BME/ECE 463. Computers in Medicine. Answers to Selected Textbook Problems

Size: px
Start display at page:

Download "BME/ECE 463. Computers in Medicine. Answers to Selected Textbook Problems"

Transcription

1 BME/ECE 463 Computers in Medicine Answers to Selected Textbook Problems W. J. Tompkins ed. Biomedical Digital Signal Processing: C Language Examples and Laboratory Experiments for the IBM PC. Englewood Cliffs, NJ: Prentice Hall,

2

3 Chapter Compare operating systems for support in developing real-time programs. Explain the relative advantages and disadvantages of each for this type of application. Summarize Figure Those closest to diagonal line like PC/DOS are most useful for real time. Single-task, single-user DOS is most suitable. o Unix OS/ o Increasing expertise o Windows 3.x PC/DOS o o CP/M Macintosh Decreasing versatility o Figure 1.11 Disk operating systems the compromise between DOS versatility and user expertise in real-time applications. 1. Explain the differences between interpreted, compiled, and integratedenvironment compiled languages. Give examples of each type. Interpreted. All or most of resources, including editor, are in memory. Character string representing program is preserved in memory and interpreted each time program is run. BASIC is a classic example. 3

4 Compiled. User s source program created by an editor is converted to.obj object or binary form and linked to.lib libraries and other.obj modules to form a runnable binary program called an executable.exe. FORTRAN, Pascal, and C are examples. Compiled, integrated environment. All resources necessary to edit, compile, link, and run a program are memory resident and can produce a runnable binary program. Thus iteration time to debug a program is less than that for a non-integrated compiled environment. 1.3 List two advantages of the C language for real-time instrumentation applications. Explain why they are important. 1 Instructions are available for low-level operations e.g., bit shifting in a high-level, structured language. Efficient object code is produced by limiting the amount of error checking and providing user flexibility and control. 3 Transportable across machines, so user does not need to continuously reinvent the wheel. 4

5 Chapter.1 What is a cardiac equivalent generator? How is it different from the actual cardiac electrical activity? Give two examples. Model of cardiac electrical activity. The actual electrical activity occurs at the microscopic level. The mathematical model is a macroscopic summary of this cellular activity. Examples are the dipole vector and multiple-dipole models..3 The heart vector of a patient is oriented as shown below at one instant of time. At this time, which of the frontal leads I, II, and III are positive-going for: RA I + LA RA I + LA II III II III + + LL a + + LL b a None. b II, III..4 A certain microprocessor-based ECG machine samples and stores only leads I and II. What other standard leads can it compute from these two? III, avr, avl, avf..5 It is well known that all six frontal leads of the ECG can be expressed in terms of any two of them. Express the augmented lead at the right arm i.e., avr in terms of leads I and II. avr " I + II 5

6 .6 Express Lead II in terms of avf and avl. II avl + 4aVF 3.7 Is it possible to express lead V6 in terms of two other leads? Is there any way to calculate V6 from a larger set of leads? No. Using a precise torso model for the subject under study, it is theoretically possible, but not practical for the general population since a single torso model is generally used for everyone..10 A cardiologist records a patient s ECG on a machine that is suspected of being defective. She notices that the QRS complex of a normal patient s ECG has a lower peak-to-peak amplitude than the one recorded on a good machine. Explain what problems in instrument bandwidth might be causing this result. Too low a cutoff frequency at the high end should be 100 Hz causes attenuation of higher-frequency waves, particularly the QRS complex..11 A cardiologist notices that the T wave of a normal patient s ECG is distorted so that it looks like a biphasic sine wave instead of a unipolar wave. Explain what problems in instrument bandwidth might be causing this problem. Too high a cutoff frequency at the low end causes a differentiation effect. A high-pass filter approximates a derivative..1 What is the electrode material that is best for recording the ECG from an ambulatory patient? Silver-silver chloride Ag Ag-Cl. 6

7 .13 A cardiotachometer uses a bandpass filter to detect the QRS complex of the ECG. What is its center frequency in Hz? How was this center frequency determined? 17 Hz. Empirically determined by NASA by studying normal astronauts..14 An engineer designs a cardiotachometer that senses the occurrence of a QRS complex with a simple amplitude threshold. It malfunctions in two patients. a One patient s ECG has baseline drift and electromyographic noise. What ECG preprocessing step would provide the most effective improvement in the design for this case? b Another patient has a T wave that is much larger than the QRS complex. This false triggers the thresholding circuit. What ECG preprocessing step would provide the most effective improvement in the design for this case? a Bandpass filter. Attenuate both low and high frequencies. b High-pass filter. Attenuate the lower-frequency T wave to accentuate the amplitude of the QRS complex..16 A typical modern microprocessor-based ECG machine samples and stores leads I, II, V1, V, V3, V4, V5, and V6. From this set of leads, calculate a lead III, b augmented lead avf. a III II " I b avf II + III II + II " I II " I 7

8 Chapter What is the purpose of using a low-pass filter prior to sampling an analog signal? To prevent alias signals. 3.9 Explain Shannon s sampling theorem. If only two samples per cycle of the highest frequency in a signal is obtained, what sort of interpolation strategy is needed to reconstruct the signal? 3.9 Must sample at a rate twice the highest frequency present in a signal. Sinusoidal interpolation. Draw one cycle of a sine wave. Locate two points equally-spaced on the sine wave. The goal is to redraw the curve that represents the sine wave knowing only those two points. One strategy is linear interpolation in which you would simply draw a straight line between the two points. But this would not be a very good approximation to the curve. Linear interpolation between points would only provide a good approximation to the curve of the sine wave if you have many points on the sine wave, say 100 sampled data points per cycle. If you know that two points on a signal represented sample points on a sine wave, the only way you could reconstruct the sine wave would be by fitting the best sine wave approximation to the two points i.e., sinusoidal interpolation A 100-Hz-bandwidth ECG signal is sampled at a rate of 500 samples per second. a Draw the approximate frequency spectrum of the new digital signal obtained after sampling, and label important points on the axes. b What is the bandwidth of the new digital signal obtained after sampling this analog signal? Explain. 8

9 a f b Infinity. After sampling, the new frequency spectrum would look something like the one above, where fc 100 Hz and fs 500 Hz, Since a new set of frequencies is produced for each integral value of the sampling frequency at fs, fs, 3fs, etc., this is an infinite number of new frequencies In order to minimize aliasing, what sampling rate should be used to sample a 400-Hz triangular wave? Explain. As high as possible because of the harmonics. Much higher than 800 samples per second sps. Any waveform that is not a pure sine wave can be represented by a sum of a set of sine waves. The less smooth a wave is, the more sine waves that are necessary to represent it. So if it s composed of straight line segments like a square wave or a triangle wave, it turns out it takes many sine waves, in fact an infinite number, to exactly represent such a signal. The set of sine waves that make up a square wave are a sine wave at the fundamental frequency of the square wave plus a sine wave of every odd harmonic. If you generate a triangle wave using DigiScope and find its power spectrum, you will find that its spectrum also has a fundamental and an infinite set of harmonics. If the highest frequency present in a signal is infinite, then you would need to use an infinite sampling frequency i.e., times the highest frequency present in the signal. 3.1 A 100-Hz full-wave-rectified sine wave is sampled at 00 samples/s. The samples are used to directly reconstruct the waveform using a digital-toanalog converter. Will the resulting waveform be a good representation of the original signal? Explain. 9

10 No. Aliasing is a potential problem. Rectification causes an infinite set of harmonics. Rectification means that you take the negative points and make them positive. This produces a sharp change in direction when you change from one half-cycle to the next half-cycle. Since this is no longer a smooth sine wave, it will take many frequencies to represent the sharp change in direction. Since there will be many more frequencies present i.e., the fundamental frequency of 100 Hz and many harmonics, sampling at only 00 Hz, twice the fundamental frequency, will not be able to represent the higher harmonics without aliasing A normal QRS complex is about 100 ms wide. a What is the American Heart Association s AHA specified sampling rate for clinical electrocardiography? b If you sample an ECG at the AHA standard sampling rate, about how many sampled data points will define a normal QRS complex? a 500 sps. b About 50 samples An ECG with a 1-mV peak-to-peak QRS amplitude and a 100-ms duration is passed through an ideal low-pass filter with a 100-Hz cutoff. The ECG is then sampled at 00 samples/s. Due to a lack of memory, every other data point is thrown away after the sampling process, so that 100 data points per second are stored. The ECG is immediately reconstructed with a digital-toanalog converter followed by a low-pass reconstruction filter. Comparing the reconstruction filter output with the original signal, comment on any differences in appearance due to a aliasing, b the sampling process itself, c the peak-to-peak amplitude, and d the clinical acceptability of such a signal. a Aliasing is a problem since the effective sampling rate is 100 sps. b Peaks and valleys will be missed. c Peak-to-peak amplitude will be attenuated. d Aliasing and peak amplitude errors will compromise the clinical information in the signal. 10

11 3.0 An IBM PC signal acquisition board with an 8-bit A/D converter is used to sample an ECG. An ECG amplifier provides a peak-to-peak signal of 1 V centered in the 0-to-5-V input range of the converter. How many bits of the A/D converter are used to represent the signal? All 8 bits. 3.1 A commercial 1-bit signal acquisition board with a ±10-V input range is used to sample an ECG. An ECG amplifier provides a peak-to-peak signal of ±1 V. How many discrete amplitude steps are used to represent the ECG signal? 410. [9 bits are required 9 51, 8 56]. 3.7 In an 8-bit successive-approximation A/D converter, what is the initial digital approximation to a signal? B 80H hexadecimal. 3.8 A 4-bit successive-approximation A/D converter gets a final approximation to a signal of What approximation did it make just prior to this final result? For an 8-bit successive approximation analog-to-digital converter, what will be the next approximation made by the converter in hexadecimal if the approximation of a 0x90 to the input signal is found to be too low, b 0x80 to the input signal is found to be too high? a 90H B. Next approximation is 98H B. b 80H B. Next approximation is 40H B. 11

12 3.34 The internal IBM PC signal acquisition board described in Appendix A is used to sample an ECG. An amplifier amplifies the ECG so that a 1-mV level uses all 1 bits of the converter. What is the smallest ECG amplitude that can be resolved in µv? 1" " µv 1

13 Chapter 4 4. If the output sequence of a digital filter is {1, 0, 0,, 0, 1} in response to a unit impulse, what is the transfer function of this filter? Hz 1+ z "3 + z "5 4.3 Draw the pole-zero plot of the filter described by the following transfer function: Hz z" z" 10 o " / 3 j " 4.4 Suppose you are given a filter with a zero at 30 on the unit circle. You are asked to use this filter as a notch filter to remove 60-Hz noise. How will you do this? Can you use the same filter as a notch filter, rejecting different frequencies? f f s 60 " sps s 30 Change the sampling frequency to control the frequency where the notch occurs. 13

14 60 Hz "" 30 o 4.5 What is the z transform of a step function having an amplitude of five {i.e., 5, 5, 5, 5, }? 1 Hz 5 " 1 z A function e at is to be applied to the input of a filter. Derive the z transform of the discrete version of this function. { } e "ant 1,e "at,e "at,e "3aT,L 1 Using the binomial theorem, Xz 1" e "at z "1 4.7 Application of a unit impulse to the input of a filter whose performance is unknown produces the output sequence {1,, 0, 0, }. What would the output sequence be if a unit step were applied? {1, 1, 1, 1, } 14

15 4.8 A digital filter has the transfer function: Hz z"1 + 6z "4 " z "7. What is the difference equation for the output, ynt? ynt xnt " T + 6xnT " 4T " xnt " 7T 4.9 A digital filter has the output sequence {1,, 3, 0, 0, 0, } when its input is the unit impulse {1, 0, 0, 0, 0, }. If its input is a unit step, what is its output sequence? {1, 3, 0, 0, 0, } 4.10 A unit impulse applied to a digital filter results in the output sequence: {3,, 3, 0, 0, 0, }. A unit step function applied to the input of the same filter would produce what output sequence? {3, 5, 8, 8, 8, 8, } 4.11 The z transform of a filter is: Hz z 4. What is its a amplitude response, b phase response, c difference equation? a H"T 4sin"T b "HT T c ynt xnt " xnt " 4 The filter s amplitude and phase responses are found by substituting e j"t for z: H "T e j4"t We could now directly substitute into this function the trigonometric relationship e j"t cos "T + j sin "T 15

16 However, a common trick prior to this substitution that leads to quick simplification of expressions such as this one is to extract a power of e as a multiplier such that the final result has two similar exponential terms with equal exponents of opposite sign e j"t e j"t e j"t H "T Now substituting trigonometric equivalent for the terms in parentheses yields H "T [ ]e j"t { } cos"t + j sin"t cos"t + j sin"t The cos "T terms cancel leaving j4sin"t e j"t H "T To put this in the form Re j " where R is the real part and " is the phase angle, we need to replace the j in this expression with its equivalent: j " e cos " + j sin " 0 + j1 j j " Replacing j with e gives + j H "T "T. - * 0-4sin"T e 0-0, / Thus the magnitude response of the filter is R, or H "T 4sin"T 16

17 The linear phase response is equal to angle ", or "HT T 4.1 The transfer function of a filter designed for a sampling rate of 800 samples/s is: Hz 1" 0.5z " z "1 A 00-Hz sine wave with a peak amplitude of 4 is applied to the input. What is the peak value of the output signal? 5 The filter s amplitude and phase responses are found by substituting e j"t for z: 1 0.5e j"t H "T e j"t Since this problem only asks for the amplitude response at a single frequency, you do not need to calculate the general equation for amplitude response. You only need to evaluate this equation at the desired frequency of 00 Hz, which corresponds to "T. Therefore, j * * j * * H"T 1 0.5e "T * e * * * Since, " j e cos " j sin 0 " j1 " j Substituting in the above Eq. H"T "T 1+ j0.5 1 j

18 Therefore, a signal of 00 Hz corresponding to this angle of "T will be multiplied this factor of 1.5 and the end result will be a peak sine wave value of 4 " A unit impulse applied to a digital filter results in the following output sequence: {1,, 3, 4, 0, 0, }. A unit step function applied to the input of the same filter would produce what output sequence? {1, 3, 6, 10, 10, 10, 10, } 4.14 The transfer function of a filter designed for a sampling rate of 600 samples/s is: Hz 1" z "1 A sinusoidal signal is applied to the input: 10 sin68t. What is the peak value of the output signal? 17.3 The filter s amplitude and phase responses are found by substituting for z: H "T 1 e j"t e j"t We could now directly substitute into this function the trigonometric relationship e j"t cos "T + j sin "T However, this question just asks what the amplitude response is for the signal, 10 sin 68t. This is a sinusoidal signal 10sin "t 10sin ft with a peak value of 10 and a frequency, f 100 need to evaluate the amplitude response for f " Hz. Therefore, we just Hz, which is 18

19 Evaluating for this frequency, we get H "T "T 3 1 e j"t * 1 cos +. -, 3 / 0 j sin +. -, 3 0 * / 1" 1 " j 3 1"1+ j 3 j1.73 So the magnitude of the gain at f 100 Hz "T is 3 H"T "T 3 j Therefore, the peak value of the input sine wave at this frequency gets multiplied by this gain, and the peak amplitude of the output sine wave becomes 10 "

20 Chapter What are the main differences between FIR and IIR filters? FIR. Finite impulse response; no feedback i.e., no recursion; all poles trivial i.e., all at z 0; Inherently stable. IIR. Infinite impulse response; feedback i.e., recursion; non-trivial poles; potentially unstable. 5.3 Why are finite-length register effects less significant in FIR filters than in IIR filters? Roundoff errors in IIR filters can modify the output sequence values since they are computed including feedback terms that are arithmetically determined. Roundoff in an IIR filter can move the poles on to the unit circle, leading to instability. FIR filters are inherently stable. 5.4 Compute and sketch the frequency response of a cascade of two Hanning filters. Does the cascade have linear phase? [ ] " H "T 1 1+ cost H T T linear 4 The amplitude and phase responses of a Hanning filter are: 1 [ 1+ cos"t ] and "HT T H "T The amplitude and phase response are of the form H" Re j" where R is the real part of the amplitude response or H"T and " is the phase response or "HT. When two filters are cascaded, their transfer functions are multiplied. For this case H " Re j Re j R e j 0

21 Therefore, the cascade of two Hanning filters would result in H "T 1 [ 1+ cost ] and "HT T 4 Thus amplitude responses multiply and phase responses add, and the overall phase response is linear. Hanning filter: Cascade of two Hanning filters: 5.5 Derive the phase response for an FIR filter with zeros located at r "1 ±. Comment. r" ± and "HT T 1

22 This problem indicates that there are four zeros. They are at z re j", z re " j, z 1 r e j", and z 1. Variable r is the radius of the pole r location and q is the angle of the zero locations. Since r must be positive, at each angle, there is one zero inside the unit circle and one zero outside the unit circle. The z transform is: e" j z " re j z " re " j z " 1 r e j z " 1 j e" r Hz z 4 * z " r e j + e " j z + r -* +,./ z " 1 r e j + e " j z + 1 -, + Hz r /. z " r cos z + r * z " cos -, / z r. Hz r Hz 1" r cos z "1 + r z " * cos - 1", / z "1 * + 1 -, / z " + r. +. The filter s amplitude and phase responses e j"t are found by substituting for z. Then substitute into H"T the trigonometric relationship z 4 z 4 e j"t cos "T + j sin "T You can then find an expression for the amplitude response H"T and the phase response "HT. 5.6 What are the trade-offs to consider when choosing the order of a leastsquares polynomial smoothing filter? r

23 The more points used in the parabolic approximation, the sharper the cutoff, but the greater the computation time. 5.9 What are the main differences between the two-point difference and threepoint central difference algorithms for approximating the derivative? The three-point derivative has a built-in smoothing function that attenuates high-frequency noise What are the three steps to designing a filter using the window method? 1 Establish desired brickwall transfer function. Find IDFT. 3 Truncate series with a window function The transfer function of the Hanning filter is H 1 z 1+ z"1 + z " a What is its gain at dc? b Three successive stages of this filter are cascaded together to give a new transfer function [that is, Hz H 1 z " H 1 z " H 1 z]. What is the overall gain of this filter at dc? c A high-pass filter is designed by subtracting the output of the Hanning filter from an all-pass filter with zero phase delay. How many zeros does the resulting filter have? Where are they located? 4 a H"T 1 dc The filter s amplitude and phase responses are found by substituting for z: H "T 1+ e j"t + e j"t 4 e j"t 3

24 We could now directly substitute into this function the trigonometric relationship e j"t cos "T + j sin "T Then we could calculate the value of the amplitude response i.e., gain for any arbitrary frequency. However, this question just asks what the amplitude response is at dc i.e., f 0 or "T 0. Therefore, we just need to evaluate the amplitude response at "T 0. Substituting this frequency into the equation above, we get H "T 1+ e j0 + e j0 "T e0 + e So the magnitude of the gain at f 0 Hz is 1. You can convert this to decibels as follows: Gain 0log db b H "T 1 dc c Hz 1" z"1 + z "1 3 4 " 1 z"1 " 1 4 z"1 zeros at z 1," 1 3 4

25 5.17 Two filters are cascaded. The first has the transfer function: H 1 z 1+ z "1 " 3z ". The second has the transfer function: H z 1" z "1. A unit impulse is applied to the input of the cascaded filters. a What is the output sequence? b What is the magnitude of the amplitude response of the cascaded filter 1 at dc? at 1/ the foldover frequency? 3 at the foldover frequency? a {1, 0, 7, 6, 0, 0, 0, } b 1 0 b 10 The filter s amplitude and phase responses are found by substituting for z: H "T 1+ e j"t 3e j"t j"t 1 e e j"t The foldover frequency is one-half the sampling rate "T. So one-half the foldover frequency is "T. * H ",, 1+ e, + j " H " * 1+ cos " j sin ", 3 cos " + -* 3e j " /, /, 1 e /,. + j sin " j " - / / /. -* / 1 cos ". j sin " -, / +. H " 1+ 0 j1 H " 4 j [ 3 1 j0 ][ 1 0 j1 ] [ ][ 1+ j] 4 j + j j6 5

26 So the magnitude of the amplitude response at one-half the foldover frequency is: H " b Two filters are cascaded. The first has the transfer function: H 1 z 1+ z "1 + z ". The second has the transfer function: H z 1" z "1. a A unit impulse is applied to the input of the cascaded filters. What is the output sequence? b What is the magnitude of the amplitude response of this cascaded filter at dc? a {1, 1, 1, 1, 0, 0, 0, } b H"T dc 0 6

27 Chapter A filter has the following output sequence in response to a unit impulse: {,4, 8, 16, }. Write its z transform in closed form i.e., as a ratio of polynomials. From the following list, indicate all the terms that describe this filter: recursive, nonrecursive, stable, unstable, FIR, IIR. " Hz 1+ z "1 recursive, unstable, IIR The output sequence is: {, 4, 8, 16, 3, } Using the binomial theorem, where v "z "1 Hz " + 4z "1 " 8z " + 16z "3 " 3z "4 + L Hz " 1" z "1 + 4z " " 8z "3 + 16z "4 + L 1 1" v 1+ v + v + v 3 + v " Hz " 1" "z "1 1+ z "1 Find the pole location by setting the denominator equal to zero: Therefore, z + 0 z " Since this filter has a pole, it is a recursive or IIR filter. It is unstable since the pole is outside the unit circle. It s clear from the output sequence that it is unstable, since the values of the output terms increase continuously in value. 7

28 6.14 The block diagrams for four digital filters are shown below. Write their a transfer functions, b difference equations a Hz 1" z"1 1" z "1 b ynt ynt " T + xnt " xnt " T 1+ 1 a Hz z"1 1" 1 b z"1 ynt 1 ynt " T + xnt + 1 xnt " T z "1 3 a Hz b ynt ynt " T + ynt " T + xnt " T 1" z "1 " z " 3 a Assign a new variable P z at the output of the summer on the left. Then and Pz Xz + Yzz "1 Yz Pzz "1 + Yzz "1 8

29 Substituting P z gives Yz Xz + Yzz "1 z "1 + Yzz "1 Xzz "1 + Yzz "1 + Yzz " Rearranging terms Finally Xzz "1 Yz 1" z "1 " z " z "1 Hz 1" z "1 " z " 1 4 a Hz 1" z "1 b ynt ynt " T + ynt " T + xnt " " z 6.16 A digital filter has a difference equation: ynt ynt " T + xnt " T. What is its output sequence in response to a unit impulse applied to its input? {0, 1, 0, 1, 0, 1, } Transforming the difference equation to the z domain gives: Yz Yzz " + Xzz "1 Then block diagram can then be drawn from this equation: Yz Xz 1 9

30 Putting the unit impulse sequence {1, 0, 0, 0, 0, } into the filter and following the signal to the output gives the output sequence {0, 1, 0, 1, 0, 1, 0, 1, 0, } The difference equation of a filter is: ynt xnt + xnt " T + ynt " T. Where are its poles and zeros located? zeros: z 0 ± j1 poles: z "1+ j0;z 1+ j0 6.0 A digital filter has two zeros located at z 0.5 and z 1, and two poles located at z 0.5 and z 0. Write an expression for a its amplitude response as a function of a single trigonometric term, and b its phase response. z "1 z " 0 Hz z " 0.5 z " 0.5 1" z"1 30

31 Substitute z e j"t : H"T 1 e j"t Then use half angles to reduce to a single trigonometric form. H"T e j "T e j "T e j "T e " j T cos T + j sin T " cos T " j sin T * +, -. / H"T e j "T jsin "T * +, -. / We want the form Re j" where R is the purely real amplitude response and θ is the purely imaginary phase response. To make the term in brackets purely real, we need to incorporate the j into the phase term. To do this, we need to use the trigonometric identity: e j" cos " + j sin " If ", e j " cos " + j sin " 0 + j1 j Therefore, we can replace j with e j " : H"T e j "T e j * sin "T +, -. / 0 e j 1 *"T sin "T +, -. / 0 31

32 H"T sin "T "HT 1 T 6. A digital filter has the block diagram shown below. a Write its transfer function. b Where are its poles and zeros located? a Hz 1+ 1 z"1 3 " 1 6 z"1 b zero: z " 1 pole: z Application of a unit impulse to the input of a filter produces the output sequence {1, 0, 1, 0, 1, 0, }. What is the difference equation for this filter? ynt xnt + ynt " T 3

33 6.6 Write the transfer functions of the following digital filters: a b c z "1 a Hz 1" 1 z"1 " z " + 1 z"3 1+ z"1 b Hz 1" z "1 1 c Hz 1+ z " + z "4 6.8 Write the amplitude response of a filter with the transfer function: Hz z" 1" z " 33

34 H"T 1 sin "T 6.30 A filter operating at a sampling frequency of 1000 samples/s has a pole at z 1/ and a zero at z 3. What is the magnitude of its amplitude response at dc? H"T "T A filter has the difference equation: ynt ynt T + xnt + xnt T. What traditional filter type best describes this filter? Integrator 6.34 The difference equation for a digital filter is: ynt xnt " axnt " T " bynt " T. Variables a and b are positive integers. What traditional type of filter is this if a 1 and a b 0.8, b b > 1? a high-pass b unstable 6.36 Write the a amplitude response, b phase response, and c difference equation for a filter with the transfer function: Hz z "1 z + 1 Hz z "1 1" z"1 z z "1 34

35 The filter s amplitude and phase responses are found by substituting for z: j"t 1 e H"T + e j"t Now substitute Giving 1 cos "T H"T + cos "T Let Then e " jt cos T " j sin T { j sin "T } { j sin "T } B sin "T A 1" cos T C + cos "T H "T A + jb C jb { } + j sin "T { } j sin "T 1 cos "T + cos "T Multiply by the complex conjugate of the denominator H "T A + jb C jb C + jb The amplitude response is AC B * + j AB + BC C + jb B + C e j"t H "T AC B + AB + BC B + C The phase response is tan 1 AB + BC "H T AC B * 35

36 Substitute the equivalents for variables A, B, and C from above, and you will get the final answer. c ynt 1 [ xnt " xnt " T " ynt " T ] 6.38 A filter operating at a sampling frequency of 00 samples/s has poles at z ±j/ and zeros at z ±1. What is the magnitude of its amplitude response at 50 Hz? H"T f 50 Hz 8 3 The sampling frequency is 00 sps and the value of the amplitude response is desired at a frequency of 50 Hz. This corresponds to an angle of " on the unit circle. z + 1 z "1 Hz z + j 1 z " j 1 z "1 z " z" z" To find the amplitude response, substitute into this equation, giving: j"t 1 e H"T 1+ 1 j"t e 4 z e j"t To find the amplitude response at "T, substitute this angle into this equation: H"T "T j"t j 1 e 1 e e j"t "T e j cos j sin cos j sin 36

37 H"T "T 1 1 j j A filter has the difference equation: ynt ynt " T " ynt " T + xnt + xnt " T. What is its transfer function? 1+ z "1 a Hz 1" z "1 + z " b unstable 6.4 A filter has a transfer function that is identical to the z transform of a unit step. A unit step is applied at its input. What is its output sequence? {1,, 3, 4, 5, } 6.44 A ramp applied to the input of digital filter produces the output sequence: {0, T, T, T, T, }. What is the transfer function of the filter? Hz 1" z " A discrete impulse function is applied to the inputs of four different filters. For each of the output sequences that follow, state whether the filter is recursive or nonrecursive. a {1,, 3, 4, 5, 6, 0, 0, 0, }, b {1, 1, 1, 1, 1, 1, }, c {1,, 4, 8, 16, }, d {1, 0.5, 0.5, 0.15, }. a is nonecursive; the rest are recursive; b and c are unstable 37

38 6.48 A differentiator is cascaded with an integrator. The differentiator uses the two-point difference algorithm: H 1 z 1" z"1 T The integrator uses trapezoidal integration: H z T 1+ z "1 1" z "1 A unit impulse is applied to the input. What is the output sequence? " 1 a, 1,0,0,0, b low-pass 6.50 A digital filter has two zeros located at z 0.5 and z 1, and a single pole located at z 0.5. Write an expression for a its amplitude response as a function of a single trigonometric term, and b its phase response. a H"T sin "T b "HT 1 T 6.5 The difference equation for a filter is: ynt " T xnt " T + xnt " 4T + 4xnT "10T. What is its transfer function, Hz? Hz 1+ z "3 + 4z "9 38

39 6.54 A digital filter has the following output sequence in response to a unit impulse: {1,, 4, 8, }. Where are its poles located? z " 6.56 The difference equation for a filter is: ynt ynt " T + xnt + xnt " T. What are the locations of its poles and zeros? zero: z " 1 pole: z 6.58 A discrete impulse function is applied to the inputs of four different filters. The output sequences of these filters are listed below. Which one of these filters has a pole outside the unit circle? a {1,, 3, 4, 5, 6, 0, 0, 0, } b {1, 1, 1, 1, 1, 1, } c {1,, 4, 8, 16, } d {1, 0.5, 0.5, 0.15, } c 6.60 What is the transfer function Hz of a filter described by the difference equation: ynt + 0.5ynT " T xnt 1 Hz z "1 39

40 Chapter Calculate expressions for the amplitude and phase response of a filter with the z transform Hz 1" z "6 H"T sin3"t "HT 3T 7.11 The numerator of a transfer function is 1" z "10. Where are its zeros located? Every 36 starting at dc f A filter has 1 zeros located on the unit circle starting at dc and equally spaced at 30 increments i.e., 1" z "1. There are three poles located at z +0.9, and z ±j. The sampling frequency is 360 samples/s. a At what frequency is the output at its maximal amplitude? b What is the gain at this frequency? a f 90 Hz b H"T f 90 Hz 4.46 The transfer function is: 1" z "1 Hz 1+ z " 1" 0.9z "1 This is what it looks like with DigiScope. 40

41 Although the maximal gain occurs in two places, when I designed the problem, my intent was to make it be maximal at "T. So this is the angle corresponding to f f s where we will find the amplitude response. 4 To find the gain at this frequency, first substitute z e j"t into the transfer function. 1 e j1"t H"T 1+ e j"t 1 0.9e j"t Now evaluate this amplitude response for the gain at "T. 41

42 H"T "T 1 e j1"t 1+ e j"t * 1 0.9e j"t * 1 e j1"t 1+ e j"t * 1 0.9e j"t * "T 1" e " j1t 1+ e " jt 1" 0.9e " jt T * 1" e " j6* 1+ e " j* 1" 0.9e " j * [ ] 1" cos6 " j sin6 { 1+ [ cos " j sin ]} 11", cos 0 * + " j0.9sin - 3 / " [ 1" j0] { 1+ ["1" j0] }{ 1" [ 0 " j0.9] } 0 0 The result is indeterminate, so we need to use L Hôpital s rule and find the derivative of the numerator and divide it by the derivative of the denominator. 1 e 1+ e j"t d Num "T d Den "T j1"t 1 0.9e j"t "" j1e " j1t 1+ e " jt " j0.9e " jt + 1" 0.9e " jt " je " jt j1e " j1t " j0.9e " jt " j0.9e " j3t " je " jt + j1.8e " j3t 4

43 1e " j1t " j0.9e " jt " je " jt + j0.9e " j3t Evaluate this expression at "T. "T d Num "T d Den "T 1e j1"t 0.9e j"t e j"t + 0.9e j3"t "T 1[ cos6" j sin6" ] * 0.9 cos " j sin " -, / cos" j sin" +. [ ] + 0.9, cos 3" * + j sin 3" - /. 1 1" j0 "0.90 " j1 " "1" j " j"1 1 j j j1.8 Multiply both numerator and denominator by the complex conjugate of the denominator. 1 + j1.8 " j1.8 4 j j.98 j The gain at "T is: Gain Gain 0log db 43

44 7.13 A digital filter has the following transfer function. a What traditional filter type best describes this filter? b What is its gain at dc? a low-pass b H"T "T0 6 1" z "6 Hz 1" z "1 1" z "1 + z " 7.14 For a filter with the following transfer function, what is the a amplitude response, b phase response, c difference equation? a H"T sin4"t cos"t b "HT 3T 1" z"8 Hz 1+ z " c ynt "ynt " T + xnt " xnt " 8T 7.15 A digital filter has the following transfer function. a What traditional filter type best describes this filter? b Draw its pole-zero plot. c Calculate its amplitude response. d What is its difference equation? Hz 1" z"8 1+ z " 44

45 a Bandpass b "" "" c H"T sin4"t cos"t d ynt "ynt " T " ynt " 4T + xnt " xnt " 8T + xnt "16T 7.16 What is the gain of a filter with the transfer function H"T "T0 6 1" z"6 Hz 1" z " What traditional filter type best describes a filter with the transfer function 1" z"56 Hz 1" z "18 45

46 Comb filter 7.18 What traditional filter type best describes a filter with the transfer function band-reject 1" z"00 Hz 1" z " 7.19 A digital filter has four zeros located at z ±1 and z ±j and four poles located at z 0, z 0, and z ±j. The sampling frequency is 800 samples/s. The maximal output amplitude occurs at what frequency? f 00 Hz 7.0 For a sampling rate of 100 samples/s, a digital filter with the following transfer function has its maximal gain at approximately what frequency in Hz? f Hz 1" z "36 Hz 1" z "1 + z " 7.1 The z transform of a filter is: Hz 1" z "360 The following sine wave is applied at the input: xt 100sin"10t. The sampling rate is 70 samples/s. a What is the peak-to-peak output of the filter? b If a unit step input is applied, what will the output amplitude be after 361 samples? c Where could poles be placed to convert this to a bandpass filter with integer coefficients? 46

47 a Since "T ft, then f 10 Hz. There are 360 zeros on the unit circle every Hz, so there is a zero at 10 Hz. Therefore, the output for any amplitude 10-Hz input is zero. b 0 c ±60, ±90, or ±10 7. What is the phase i.e., group delay in milliseconds through the following filter which operates at 00 samples/sec? 45 ms 49T 1" z"100 Hz 1" z " 7.3 A filter has 8 zeros located on the unit circle starting at dc and equally spaced at 45 increments. There are two poles located at z ±j. The sampling frequency is 360 samples/s. What is the gain of the filter? Gain 4 47

48 Chapter What are the main advantages of adaptive filters over fixed filters? Adaptive filters can continuously learn and change characteristics as the noise characteristics of the signal change. 8.7 What are the costs and benefits of using different step sizes in the 60-Hz sine wave algorithm? A smaller step size requires a longer time to adaptively change in response to changes in the signal. If the step size is too small, the filter may never adapt. Too large a step size will not permit the filter to track a signal. 8.8 Explain how the 60-Hz sine wave algorithm adapts to the phase of the noise. Adjusting the trajectory of the estimated noise signal modifies both the amplitude and phase of estimated signal. 8.9 The adaptive 60-Hz filter calculates a function f nt + T [ xnt + T " ent + T ] " [ xnt " ent ] If this function is less than zero, how does the algorithm adjust the future estimate, ent + T? ReducesenT + T by a small amount d The adaptive 60-Hz filter uses the following equation to estimate the noise: ent + T NenT " ent " T If the future estimate is found to be too high, what adjustment is made to a ent T, b ent + T. c Write the equation for N and explain the terms of the equation. 48

49 a ent " T is NEVER adjusted. b If the future estimate is found to be too high i.e., f nt + T < 0, then ent + T is DECREASED by a small amount: ent + T ent + T " d c N cos "f f s f is the noise frequency; f s is the sampling frequency 8.11 The adaptive 60-Hz filter calculates the function f nt + T [ xnt + T " ent + T ] " [ xnt " ent ] It adjusts the future estimate ent + T based on whether this function is greater than, less than, or equal to zero. Use a drawing and explain why the function could not be simplified to f nt + T xnt + T " ent + T. The original definition of the estimated noise ent did not include the dc level. This equation eliminates dc. 49

Infinite Impulse Response Filters

Infinite Impulse Response Filters 6 Infinite Impulse Response Filters Ren Zhou In this chapter we introduce the analysis and design of infinite impulse response (IIR) digital filters that have the potential of sharp rolloffs (Tompkins

More information

Basics of Digital Filtering

Basics of Digital Filtering 4 Basics of Digital Filtering Willis J. Tompkins and Pradeep Tagare In this chapter we introduce the concept of digital filtering and look at the advantages, disadvantages, and differences between analog

More information

Integer Filters. Jon D. Pfeffer

Integer Filters. Jon D. Pfeffer 7 Integer Filters Jon D. Pfeffer When digital filters must operate in a real-time environment, many filter designs become unsatisfactory due to the amount of required computation time. A considerable reduction

More information

BIOMEDICAL DIGITAL SIGNAL PROCESSING

BIOMEDICAL DIGITAL SIGNAL PROCESSING BIOMEDICAL DIGITAL SIGNAL PROCESSING C-Language Examples and Laboratory Experiments for the IBM PC WILLIS J. TOMPKINS Editor University of Wisconsin-Madison 2000 by Willis J. Tompkins This book was previously

More information

Biosignal filtering and artifact rejection. Biosignal processing I, S Autumn 2017

Biosignal filtering and artifact rejection. Biosignal processing I, S Autumn 2017 Biosignal filtering and artifact rejection Biosignal processing I, 52273S Autumn 207 Motivation ) Artifact removal power line non-stationarity due to baseline variation muscle or eye movement artifacts

More information

Digital Filters IIR (& Their Corresponding Analog Filters) Week Date Lecture Title

Digital Filters IIR (& Their Corresponding Analog Filters) Week Date Lecture Title http://elec3004.com Digital Filters IIR (& Their Corresponding Analog Filters) 2017 School of Information Technology and Electrical Engineering at The University of Queensland Lecture Schedule: Week Date

More information

Biosignal filtering and artifact rejection. Biosignal processing, S Autumn 2012

Biosignal filtering and artifact rejection. Biosignal processing, S Autumn 2012 Biosignal filtering and artifact rejection Biosignal processing, 521273S Autumn 2012 Motivation 1) Artifact removal: for example power line non-stationarity due to baseline variation muscle or eye movement

More information

Digital Filtering: Realization

Digital Filtering: Realization Digital Filtering: Realization Digital Filtering: Matlab Implementation: 3-tap (2 nd order) IIR filter 1 Transfer Function Differential Equation: z- Transform: Transfer Function: 2 Example: Transfer Function

More information

II Year (04 Semester) EE6403 Discrete Time Systems and Signal Processing

II Year (04 Semester) EE6403 Discrete Time Systems and Signal Processing Class Subject Code Subject II Year (04 Semester) EE6403 Discrete Time Systems and Signal Processing 1.CONTENT LIST: Introduction to Unit I - Signals and Systems 2. SKILLS ADDRESSED: Listening 3. OBJECTIVE

More information

Module 3 : Sampling and Reconstruction Problem Set 3

Module 3 : Sampling and Reconstruction Problem Set 3 Module 3 : Sampling and Reconstruction Problem Set 3 Problem 1 Shown in figure below is a system in which the sampling signal is an impulse train with alternating sign. The sampling signal p(t), the Fourier

More information

Biomedical Signals. Signals and Images in Medicine Dr Nabeel Anwar

Biomedical Signals. Signals and Images in Medicine Dr Nabeel Anwar Biomedical Signals Signals and Images in Medicine Dr Nabeel Anwar Noise Removal: Time Domain Techniques 1. Synchronized Averaging (covered in lecture 1) 2. Moving Average Filters (today s topic) 3. Derivative

More information

6 Sampling. Sampling. The principles of sampling, especially the benefits of coherent sampling

6 Sampling. Sampling. The principles of sampling, especially the benefits of coherent sampling Note: Printed Manuals 6 are not in Color Objectives This chapter explains the following: The principles of sampling, especially the benefits of coherent sampling How to apply sampling principles in a test

More information

16.30 Learning Objectives and Practice Problems - - Lectures 16 through 20

16.30 Learning Objectives and Practice Problems - - Lectures 16 through 20 16.30 Learning Objectives and Practice Problems - - Lectures 16 through 20 IV. Lectures 16-20 IVA : Sampling, Aliasing, and Reconstruction JVV 9.5, Lecture Notes on Shannon - Understand the mathematical

More information

Chapter 7. Introduction. Analog Signal and Discrete Time Series. Sampling, Digital Devices, and Data Acquisition

Chapter 7. Introduction. Analog Signal and Discrete Time Series. Sampling, Digital Devices, and Data Acquisition Chapter 7 Sampling, Digital Devices, and Data Acquisition Material from Theory and Design for Mechanical Measurements; Figliola, Third Edition Introduction Integrating analog electrical transducers with

More information

EE 422G - Signals and Systems Laboratory

EE 422G - Signals and Systems Laboratory EE 422G - Signals and Systems Laboratory Lab 3 FIR Filters Written by Kevin D. Donohue Department of Electrical and Computer Engineering University of Kentucky Lexington, KY 40506 September 19, 2015 Objectives:

More information

Biomedical Instrumentation (BME420 ) Chapter 6: Biopotential Amplifiers John G. Webster 4 th Edition

Biomedical Instrumentation (BME420 ) Chapter 6: Biopotential Amplifiers John G. Webster 4 th Edition Biomedical Instrumentation (BME420 ) Chapter 6: Biopotential Amplifiers John G. Webster 4 th Edition Dr. Qasem Qananwah BME 420 Department of Biomedical Systems and Informatics Engineering 1 Biopotential

More information

Signal Processing. Naureen Ghani. December 9, 2017

Signal Processing. Naureen Ghani. December 9, 2017 Signal Processing Naureen Ghani December 9, 27 Introduction Signal processing is used to enhance signal components in noisy measurements. It is especially important in analyzing time-series data in neuroscience.

More information

Signals A Preliminary Discussion EE442 Analog & Digital Communication Systems Lecture 2

Signals A Preliminary Discussion EE442 Analog & Digital Communication Systems Lecture 2 Signals A Preliminary Discussion EE442 Analog & Digital Communication Systems Lecture 2 The Fourier transform of single pulse is the sinc function. EE 442 Signal Preliminaries 1 Communication Systems and

More information

Discrete-Time Signal Processing (DTSP) v14

Discrete-Time Signal Processing (DTSP) v14 EE 392 Laboratory 5-1 Discrete-Time Signal Processing (DTSP) v14 Safety - Voltages used here are less than 15 V and normally do not present a risk of shock. Objective: To study impulse response and the

More information

ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015

ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015 Purdue University: ECE438 - Digital Signal Processing with Applications 1 ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015 1 Introduction

More information

SECTION 7: FREQUENCY DOMAIN ANALYSIS. MAE 3401 Modeling and Simulation

SECTION 7: FREQUENCY DOMAIN ANALYSIS. MAE 3401 Modeling and Simulation SECTION 7: FREQUENCY DOMAIN ANALYSIS MAE 3401 Modeling and Simulation 2 Response to Sinusoidal Inputs Frequency Domain Analysis Introduction 3 We ve looked at system impulse and step responses Also interested

More information

EECS 452 Midterm Exam (solns) Fall 2012

EECS 452 Midterm Exam (solns) Fall 2012 EECS 452 Midterm Exam (solns) Fall 2012 Name: unique name: Sign the honor code: I have neither given nor received aid on this exam nor observed anyone else doing so. Scores: # Points Section I /40 Section

More information

Signals. Continuous valued or discrete valued Can the signal take any value or only discrete values?

Signals. Continuous valued or discrete valued Can the signal take any value or only discrete values? Signals Continuous time or discrete time Is the signal continuous or sampled in time? Continuous valued or discrete valued Can the signal take any value or only discrete values? Deterministic versus random

More information

Laboratory Assignment 4. Fourier Sound Synthesis

Laboratory Assignment 4. Fourier Sound Synthesis Laboratory Assignment 4 Fourier Sound Synthesis PURPOSE This lab investigates how to use a computer to evaluate the Fourier series for periodic signals and to synthesize audio signals from Fourier series

More information

Music 270a: Fundamentals of Digital Audio and Discrete-Time Signals

Music 270a: Fundamentals of Digital Audio and Discrete-Time Signals Music 270a: Fundamentals of Digital Audio and Discrete-Time Signals Tamara Smyth, trsmyth@ucsd.edu Department of Music, University of California, San Diego October 3, 2016 1 Continuous vs. Discrete signals

More information

DSP Laboratory (EELE 4110) Lab#10 Finite Impulse Response (FIR) Filters

DSP Laboratory (EELE 4110) Lab#10 Finite Impulse Response (FIR) Filters Islamic University of Gaza OBJECTIVES: Faculty of Engineering Electrical Engineering Department Spring-2011 DSP Laboratory (EELE 4110) Lab#10 Finite Impulse Response (FIR) Filters To demonstrate the concept

More information

Digital Processing of Continuous-Time Signals

Digital Processing of Continuous-Time Signals Chapter 4 Digital Processing of Continuous-Time Signals 清大電機系林嘉文 cwlin@ee.nthu.edu.tw 03-5731152 Original PowerPoint slides prepared by S. K. Mitra 4-1-1 Digital Processing of Continuous-Time Signals Digital

More information

UNIT IV FIR FILTER DESIGN 1. How phase distortion and delay distortion are introduced? The phase distortion is introduced when the phase characteristics of a filter is nonlinear within the desired frequency

More information

NH 67, Karur Trichy Highways, Puliyur C.F, Karur District DEPARTMENT OF INFORMATION TECHNOLOGY DIGITAL SIGNAL PROCESSING UNIT 3

NH 67, Karur Trichy Highways, Puliyur C.F, Karur District DEPARTMENT OF INFORMATION TECHNOLOGY DIGITAL SIGNAL PROCESSING UNIT 3 NH 67, Karur Trichy Highways, Puliyur C.F, 639 114 Karur District DEPARTMENT OF INFORMATION TECHNOLOGY DIGITAL SIGNAL PROCESSING UNIT 3 IIR FILTER DESIGN Structure of IIR System design of Discrete time

More information

Digital Processing of

Digital Processing of Chapter 4 Digital Processing of Continuous-Time Signals 清大電機系林嘉文 cwlin@ee.nthu.edu.tw 03-5731152 Original PowerPoint slides prepared by S. K. Mitra 4-1-1 Digital Processing of Continuous-Time Signals Digital

More information

Digital Filters FIR and IIR Systems

Digital Filters FIR and IIR Systems Digital Filters FIR and IIR Systems ELEC 3004: Systems: Signals & Controls Dr. Surya Singh (Some material adapted from courses by Russ Tedrake and Elena Punskaya) Lecture 16 elec3004@itee.uq.edu.au http://robotics.itee.uq.edu.au/~elec3004/

More information

EE482: Digital Signal Processing Applications

EE482: Digital Signal Processing Applications Professor Brendan Morris, SEB 3216, brendan.morris@unlv.edu EE482: Digital Signal Processing Applications Spring 2014 TTh 14:30-15:45 CBC C222 Lecture 01 Introduction 14/01/21 http://www.ee.unlv.edu/~b1morris/ee482/

More information

ANALOGUE AND DIGITAL COMMUNICATION

ANALOGUE AND DIGITAL COMMUNICATION ANALOGUE AND DIGITAL COMMUNICATION Syed M. Zafi S. Shah Umair M. Qureshi Lecture xxx: Analogue to Digital Conversion Topics Pulse Modulation Systems Advantages & Disadvantages Pulse Code Modulation Pulse

More information

TRANSFORMS / WAVELETS

TRANSFORMS / WAVELETS RANSFORMS / WAVELES ransform Analysis Signal processing using a transform analysis for calculations is a technique used to simplify or accelerate problem solution. For example, instead of dividing two

More information

Copyright S. K. Mitra

Copyright S. K. Mitra 1 In many applications, a discrete-time signal x[n] is split into a number of subband signals by means of an analysis filter bank The subband signals are then processed Finally, the processed subband signals

More information

The Fundamentals of Mixed Signal Testing

The Fundamentals of Mixed Signal Testing The Fundamentals of Mixed Signal Testing Course Information The Fundamentals of Mixed Signal Testing course is designed to provide the foundation of knowledge that is required for testing modern mixed

More information

Chapter 5 Window Functions. periodic with a period of N (number of samples). This is observed in table (3.1).

Chapter 5 Window Functions. periodic with a period of N (number of samples). This is observed in table (3.1). Chapter 5 Window Functions 5.1 Introduction As discussed in section (3.7.5), the DTFS assumes that the input waveform is periodic with a period of N (number of samples). This is observed in table (3.1).

More information

CHAPTER 6 INTRODUCTION TO SYSTEM IDENTIFICATION

CHAPTER 6 INTRODUCTION TO SYSTEM IDENTIFICATION CHAPTER 6 INTRODUCTION TO SYSTEM IDENTIFICATION Broadly speaking, system identification is the art and science of using measurements obtained from a system to characterize the system. The characterization

More information

Computer Networks. Practice Set I. Dr. Hussein Al-Bahadili

Computer Networks. Practice Set I. Dr. Hussein Al-Bahadili بسم االله الرحمن الرحيم Computer Networks Practice Set I Dr. Hussein Al-Bahadili (1/11) Q. Circle the right answer. 1. Before data can be transmitted, they must be transformed to. (a) Periodic signals

More information

CMPT 318: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals

CMPT 318: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals CMPT 318: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University January 16, 2006 1 Continuous vs. Discrete

More information

Digital Signal Processing

Digital Signal Processing Digital Signal Processing System Analysis and Design Paulo S. R. Diniz Eduardo A. B. da Silva and Sergio L. Netto Federal University of Rio de Janeiro CAMBRIDGE UNIVERSITY PRESS Preface page xv Introduction

More information

Outline. Discrete time signals. Impulse sampling z-transform Frequency response Stability INF4420. Jørgen Andreas Michaelsen Spring / 37 2 / 37

Outline. Discrete time signals. Impulse sampling z-transform Frequency response Stability INF4420. Jørgen Andreas Michaelsen Spring / 37 2 / 37 INF4420 Discrete time signals Jørgen Andreas Michaelsen Spring 2013 1 / 37 Outline Impulse sampling z-transform Frequency response Stability Spring 2013 Discrete time signals 2 2 / 37 Introduction More

More information

Department of Electronic Engineering NED University of Engineering & Technology. LABORATORY WORKBOOK For the Course SIGNALS & SYSTEMS (TC-202)

Department of Electronic Engineering NED University of Engineering & Technology. LABORATORY WORKBOOK For the Course SIGNALS & SYSTEMS (TC-202) Department of Electronic Engineering NED University of Engineering & Technology LABORATORY WORKBOOK For the Course SIGNALS & SYSTEMS (TC-202) Instructor Name: Student Name: Roll Number: Semester: Batch:

More information

Continuous vs. Discrete signals. Sampling. Analog to Digital Conversion. CMPT 368: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals

Continuous vs. Discrete signals. Sampling. Analog to Digital Conversion. CMPT 368: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals Continuous vs. Discrete signals CMPT 368: Lecture 4 Fundamentals of Digital Audio, Discrete-Time Signals Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University January 22,

More information

ENGR 210 Lab 12: Sampling and Aliasing

ENGR 210 Lab 12: Sampling and Aliasing ENGR 21 Lab 12: Sampling and Aliasing In the previous lab you examined how A/D converters actually work. In this lab we will consider some of the consequences of how fast you sample and of the signal processing

More information

Understanding Digital Signal Processing

Understanding Digital Signal Processing Understanding Digital Signal Processing Richard G. Lyons PRENTICE HALL PTR PRENTICE HALL Professional Technical Reference Upper Saddle River, New Jersey 07458 www.photr,com Contents Preface xi 1 DISCRETE

More information

INTRODUCTION DIGITAL SIGNAL PROCESSING

INTRODUCTION DIGITAL SIGNAL PROCESSING INTRODUCTION TO DIGITAL SIGNAL PROCESSING by Dr. James Hahn Adjunct Professor Washington University St. Louis 1/22/11 11:28 AM INTRODUCTION Purpose/objective of the course: To provide sufficient background

More information

Design Implementation Description for the Digital Frequency Oscillator

Design Implementation Description for the Digital Frequency Oscillator Appendix A Design Implementation Description for the Frequency Oscillator A.1 Input Front End The input data front end accepts either analog single ended or differential inputs (figure A-1). The input

More information

ECE 6560 Multirate Signal Processing Chapter 11

ECE 6560 Multirate Signal Processing Chapter 11 ultirate Signal Processing Chapter Dr. Bradley J. Bauin Western ichigan University College of Engineering and Applied Sciences Department of Electrical and Computer Engineering 903 W. ichigan Ave. Kalamaoo

More information

Subtractive Synthesis without Filters

Subtractive Synthesis without Filters Subtractive Synthesis without Filters John Lazzaro and John Wawrzynek Computer Science Division UC Berkeley lazzaro@cs.berkeley.edu, johnw@cs.berkeley.edu 1. Introduction The earliest commercially successful

More information

Basic Signals and Systems

Basic Signals and Systems Chapter 2 Basic Signals and Systems A large part of this chapter is taken from: C.S. Burrus, J.H. McClellan, A.V. Oppenheim, T.W. Parks, R.W. Schafer, and H. W. Schüssler: Computer-based exercises for

More information

Design of FIR Filters

Design of FIR Filters Design of FIR Filters Elena Punskaya www-sigproc.eng.cam.ac.uk/~op205 Some material adapted from courses by Prof. Simon Godsill, Dr. Arnaud Doucet, Dr. Malcolm Macleod and Prof. Peter Rayner 1 FIR as a

More information

Instruction Manual for Concept Simulators. Signals and Systems. M. J. Roberts

Instruction Manual for Concept Simulators. Signals and Systems. M. J. Roberts Instruction Manual for Concept Simulators that accompany the book Signals and Systems by M. J. Roberts March 2004 - All Rights Reserved Table of Contents I. Loading and Running the Simulators II. Continuous-Time

More information

2) How fast can we implement these in a system

2) How fast can we implement these in a system Filtration Now that we have looked at the concept of interpolation we have seen practically that a "digital filter" (hold, or interpolate) can affect the frequency response of the overall system. We need

More information

Laboratory Assignment 1 Sampling Phenomena

Laboratory Assignment 1 Sampling Phenomena 1 Main Topics Signal Acquisition Audio Processing Aliasing, Anti-Aliasing Filters Laboratory Assignment 1 Sampling Phenomena 2.171 Analysis and Design of Digital Control Systems Digital Filter Design and

More information

SIGMA-DELTA CONVERTER

SIGMA-DELTA CONVERTER SIGMA-DELTA CONVERTER (1995: Pacífico R. Concetti Western A. Geophysical-Argentina) The Sigma-Delta A/D Converter is not new in electronic engineering since it has been previously used as part of many

More information

Laboratory Assignment 5 Amplitude Modulation

Laboratory Assignment 5 Amplitude Modulation Laboratory Assignment 5 Amplitude Modulation PURPOSE In this assignment, you will explore the use of digital computers for the analysis, design, synthesis, and simulation of an amplitude modulation (AM)

More information

Appendix B. Design Implementation Description For The Digital Frequency Demodulator

Appendix B. Design Implementation Description For The Digital Frequency Demodulator Appendix B Design Implementation Description For The Digital Frequency Demodulator The DFD design implementation is divided into four sections: 1. Analog front end to signal condition and digitize the

More information

Chapter-2 SAMPLING PROCESS

Chapter-2 SAMPLING PROCESS Chapter-2 SAMPLING PROCESS SAMPLING: A message signal may originate from a digital or analog source. If the message signal is analog in nature, then it has to be converted into digital form before it can

More information

Digital Video and Audio Processing. Winter term 2002/ 2003 Computer-based exercises

Digital Video and Audio Processing. Winter term 2002/ 2003 Computer-based exercises Digital Video and Audio Processing Winter term 2002/ 2003 Computer-based exercises Rudolf Mester Institut für Angewandte Physik Johann Wolfgang Goethe-Universität Frankfurt am Main 6th November 2002 Chapter

More information

AN-348(1) OBTAINING SINUSOIDAL WAVEFORMS

AN-348(1) OBTAINING SINUSOIDAL WAVEFORMS ELECTRONOTES APPLICATION NOTE NO. 348 1016 HanshawRd. Ithaca, NY 14850 July 1998 (607)-257-8010 CONTRASTING SINEWAVE GENERATION IN THE ANALOG AND DIGITAL CASES OBTAINING SINUSOIDAL WAVEFORMS Nothing is

More information

Part One. Efficient Digital Filters COPYRIGHTED MATERIAL

Part One. Efficient Digital Filters COPYRIGHTED MATERIAL Part One Efficient Digital Filters COPYRIGHTED MATERIAL Chapter 1 Lost Knowledge Refound: Sharpened FIR Filters Matthew Donadio Night Kitchen Interactive What would you do in the following situation?

More information

Signal Processing for Digitizers

Signal Processing for Digitizers Signal Processing for Digitizers Modular digitizers allow accurate, high resolution data acquisition that can be quickly transferred to a host computer. Signal processing functions, applied in the digitizer

More information

Laboratory Assignment 2 Signal Sampling, Manipulation, and Playback

Laboratory Assignment 2 Signal Sampling, Manipulation, and Playback Laboratory Assignment 2 Signal Sampling, Manipulation, and Playback PURPOSE This lab will introduce you to the laboratory equipment and the software that allows you to link your computer to the hardware.

More information

Lecture 7 Frequency Modulation

Lecture 7 Frequency Modulation Lecture 7 Frequency Modulation Fundamentals of Digital Signal Processing Spring, 2012 Wei-Ta Chu 2012/3/15 1 Time-Frequency Spectrum We have seen that a wide range of interesting waveforms can be synthesized

More information

System on a Chip. Prof. Dr. Michael Kraft

System on a Chip. Prof. Dr. Michael Kraft System on a Chip Prof. Dr. Michael Kraft Lecture 5: Data Conversion ADC Background/Theory Examples Background Physical systems are typically analogue To apply digital signal processing, the analogue signal

More information

LECTURER NOTE SMJE3163 DSP

LECTURER NOTE SMJE3163 DSP LECTURER NOTE SMJE363 DSP (04/05-) ------------------------------------------------------------------------- Week3 IIR Filter Design -------------------------------------------------------------------------

More information

A DSP IMPLEMENTED DIGITAL FM MULTIPLEXING SYSTEM

A DSP IMPLEMENTED DIGITAL FM MULTIPLEXING SYSTEM A DSP IMPLEMENTED DIGITAL FM MULTIPLEXING SYSTEM Item Type text; Proceedings Authors Rosenthal, Glenn K. Publisher International Foundation for Telemetering Journal International Telemetering Conference

More information

Electrical & Computer Engineering Technology

Electrical & Computer Engineering Technology Electrical & Computer Engineering Technology EET 419C Digital Signal Processing Laboratory Experiments by Masood Ejaz Experiment # 1 Quantization of Analog Signals and Calculation of Quantized noise Objective:

More information

Digital Signal Processing. VO Embedded Systems Engineering Armin Wasicek WS 2009/10

Digital Signal Processing. VO Embedded Systems Engineering Armin Wasicek WS 2009/10 Digital Signal Processing VO Embedded Systems Engineering Armin Wasicek WS 2009/10 Overview Signals and Systems Processing of Signals Display of Signals Digital Signal Processors Common Signal Processing

More information

Lecture Schedule: Week Date Lecture Title

Lecture Schedule: Week Date Lecture Title http://elec3004.org Sampling & More 2014 School of Information Technology and Electrical Engineering at The University of Queensland Lecture Schedule: Week Date Lecture Title 1 2-Mar Introduction 3-Mar

More information

TABLE OF CONTENTS TOPIC NUMBER NAME OF THE TOPIC 1. OVERVIEW OF SIGNALS & SYSTEMS 2. ANALYSIS OF LTI SYSTEMS- Z TRANSFORM 3. ANALYSIS OF FT, DFT AND FFT SIGNALS 4. DIGITAL FILTERS CONCEPTS & DESIGN 5.

More information

Introduction to Communications Part Two: Physical Layer Ch3: Data & Signals

Introduction to Communications Part Two: Physical Layer Ch3: Data & Signals Introduction to Communications Part Two: Physical Layer Ch3: Data & Signals Kuang Chiu Huang TCM NCKU Spring/2008 Goals of This Class Through the lecture of fundamental information for data and signals,

More information

A slope of a line is the ratio between the change in a vertical distance (rise) to the change in a horizontal

A slope of a line is the ratio between the change in a vertical distance (rise) to the change in a horizontal The Slope of a Line (2.2) Find the slope of a line given two points on the line (Objective #1) A slope of a line is the ratio between the change in a vertical distance (rise) to the change in a horizontal

More information

Corso di DATI e SEGNALI BIOMEDICI 1. Carmelina Ruggiero Laboratorio MedInfo

Corso di DATI e SEGNALI BIOMEDICI 1. Carmelina Ruggiero Laboratorio MedInfo Corso di DATI e SEGNALI BIOMEDICI 1 Carmelina Ruggiero Laboratorio MedInfo Digital Filters Function of a Filter In signal processing, the functions of a filter are: to remove unwanted parts of the signal,

More information

(i) Understanding of the characteristics of linear-phase finite impulse response (FIR) filters

(i) Understanding of the characteristics of linear-phase finite impulse response (FIR) filters FIR Filter Design Chapter Intended Learning Outcomes: (i) Understanding of the characteristics of linear-phase finite impulse response (FIR) filters (ii) Ability to design linear-phase FIR filters according

More information

Question 1 Draw a block diagram to illustrate how the data was acquired. Be sure to include important parameter values

Question 1 Draw a block diagram to illustrate how the data was acquired. Be sure to include important parameter values Data acquisition Question 1 Draw a block diagram to illustrate how the data was acquired. Be sure to include important parameter values The block diagram illustrating how the signal was acquired is shown

More information

Signals and Systems Lecture 6: Fourier Applications

Signals and Systems Lecture 6: Fourier Applications Signals and Systems Lecture 6: Fourier Applications Farzaneh Abdollahi Department of Electrical Engineering Amirkabir University of Technology Winter 2012 arzaneh Abdollahi Signal and Systems Lecture 6

More information

EE 311 February 13 and 15, 2019 Lecture 10

EE 311 February 13 and 15, 2019 Lecture 10 EE 311 February 13 and 15, 219 Lecture 1 Figure 4.22 The top figure shows a quantized sinusoid as the darker stair stepped curve. The bottom figure shows the quantization error. The quantized signal to

More information

Biomedical Instrumentation B2. Dealing with noise

Biomedical Instrumentation B2. Dealing with noise Biomedical Instrumentation B2. Dealing with noise B18/BME2 Dr Gari Clifford Noise & artifact in biomedical signals Ambient / power line interference: 50 ±0.2 Hz mains noise (or 60 Hz in many data sets)

More information

Lab S-9: Interference Removal from Electro-Cardiogram (ECG) Signals

Lab S-9: Interference Removal from Electro-Cardiogram (ECG) Signals DSP First, 2e Signal Processing First Lab S-9: Interference Removal from Electro-Cardiogram (ECG) Signals Pre-Lab: Read the Pre-Lab and do all the exercises in the Pre-Lab section prior to attending lab.

More information

SAMPLING AND RECONSTRUCTING SIGNALS

SAMPLING AND RECONSTRUCTING SIGNALS CHAPTER 3 SAMPLING AND RECONSTRUCTING SIGNALS Many DSP applications begin with analog signals. In order to process these analog signals, the signals must first be sampled and converted to digital signals.

More information

Electrocardiogram (ECG)

Electrocardiogram (ECG) Vectors and ECG s Vectors and ECG s 2 Electrocardiogram (ECG) Depolarization wave passes through the heart and the electrical currents pass into surrounding tissues. Small part of the extracellular current

More information

Advanced Digital Signal Processing Part 5: Digital Filters

Advanced Digital Signal Processing Part 5: Digital Filters Advanced Digital Signal Processing Part 5: Digital Filters Gerhard Schmidt Christian-Albrechts-Universität zu Kiel Faculty of Engineering Institute of Electrical and Information Engineering Digital Signal

More information

Subtractive Synthesis. Describing a Filter. Filters. CMPT 468: Subtractive Synthesis

Subtractive Synthesis. Describing a Filter. Filters. CMPT 468: Subtractive Synthesis Subtractive Synthesis CMPT 468: Subtractive Synthesis Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University November, 23 Additive synthesis involves building the sound by

More information

1. Find the magnitude and phase response of an FIR filter represented by the difference equation y(n)= 0.5 x(n) x(n-1)

1. Find the magnitude and phase response of an FIR filter represented by the difference equation y(n)= 0.5 x(n) x(n-1) Lecture 5 1.8.1 FIR Filters FIR filters have impulse responses of finite lengths. In FIR filters the present output depends only on the past and present values of the input sequence but not on the previous

More information

Positive Feedback and Oscillators

Positive Feedback and Oscillators Physics 3330 Experiment #5 Fall 2011 Positive Feedback and Oscillators Purpose In this experiment we will study how spontaneous oscillations may be caused by positive feedback. You will construct an active

More information

Lecture 3 Review of Signals and Systems: Part 2. EE4900/EE6720 Digital Communications

Lecture 3 Review of Signals and Systems: Part 2. EE4900/EE6720 Digital Communications EE4900/EE6720: Digital Communications 1 Lecture 3 Review of Signals and Systems: Part 2 Block Diagrams of Communication System Digital Communication System 2 Informatio n (sound, video, text, data, ) Transducer

More information

System analysis and signal processing

System analysis and signal processing System analysis and signal processing with emphasis on the use of MATLAB PHILIP DENBIGH University of Sussex ADDISON-WESLEY Harlow, England Reading, Massachusetts Menlow Park, California New York Don Mills,

More information

Lecture 17 z-transforms 2

Lecture 17 z-transforms 2 Lecture 17 z-transforms 2 Fundamentals of Digital Signal Processing Spring, 2012 Wei-Ta Chu 2012/5/3 1 Factoring z-polynomials We can also factor z-transform polynomials to break down a large system into

More information

Lecture 4 Biosignal Processing. Digital Signal Processing and Analysis in Biomedical Systems

Lecture 4 Biosignal Processing. Digital Signal Processing and Analysis in Biomedical Systems Lecture 4 Biosignal Processing Digital Signal Processing and Analysis in Biomedical Systems Contents - Preprocessing as first step of signal analysis - Biosignal acquisition - ADC - Filtration (linear,

More information

Bibliography. Practical Signal Processing and Its Applications Downloaded from

Bibliography. Practical Signal Processing and Its Applications Downloaded from Bibliography Practical Signal Processing and Its Applications Downloaded from www.worldscientific.com Abramowitz, Milton, and Irene A. Stegun. Handbook of mathematical functions: with formulas, graphs,

More information

PYKC 27 Feb 2017 EA2.3 Electronics 2 Lecture PYKC 27 Feb 2017 EA2.3 Electronics 2 Lecture 11-2

PYKC 27 Feb 2017 EA2.3 Electronics 2 Lecture PYKC 27 Feb 2017 EA2.3 Electronics 2 Lecture 11-2 In this lecture, I will introduce the mathematical model for discrete time signals as sequence of samples. You will also take a first look at a useful alternative representation of discrete signals known

More information

(i) Understanding of the characteristics of linear-phase finite impulse response (FIR) filters

(i) Understanding of the characteristics of linear-phase finite impulse response (FIR) filters FIR Filter Design Chapter Intended Learning Outcomes: (i) Understanding of the characteristics of linear-phase finite impulse response (FIR) filters (ii) Ability to design linear-phase FIR filters according

More information

Michael F. Toner, et. al.. "Distortion Measurement." Copyright 2000 CRC Press LLC. <

Michael F. Toner, et. al.. Distortion Measurement. Copyright 2000 CRC Press LLC. < Michael F. Toner, et. al.. "Distortion Measurement." Copyright CRC Press LLC. . Distortion Measurement Michael F. Toner Nortel Networks Gordon W. Roberts McGill University 53.1

More information

Volume 3 Signal Processing Reference Manual

Volume 3 Signal Processing Reference Manual Contents Volume 3 Signal Processing Reference Manual Contents 1 Sampling analogue signals 1.1 Introduction...1-1 1.2 Selecting a sampling speed...1-1 1.3 References...1-5 2 Digital filters 2.1 Introduction...2-1

More information

THE CITADEL THE MILITARY COLLEGE OF SOUTH CAROLINA. Department of Electrical and Computer Engineering. ELEC 423 Digital Signal Processing

THE CITADEL THE MILITARY COLLEGE OF SOUTH CAROLINA. Department of Electrical and Computer Engineering. ELEC 423 Digital Signal Processing THE CITADEL THE MILITARY COLLEGE OF SOUTH CAROLINA Department of Electrical and Computer Engineering ELEC 423 Digital Signal Processing Project 2 Due date: November 12 th, 2013 I) Introduction In ELEC

More information

DIGITAL FILTERING OF MULTIPLE ANALOG CHANNELS

DIGITAL FILTERING OF MULTIPLE ANALOG CHANNELS DIGITAL FILTERING OF MULTIPLE ANALOG CHANNELS Item Type text; Proceedings Authors Hicks, William T. Publisher International Foundation for Telemetering Journal International Telemetering Conference Proceedings

More information

EE 470 Signals and Systems

EE 470 Signals and Systems EE 470 Signals and Systems 9. Introduction to the Design of Discrete Filters Prof. Yasser Mostafa Kadah Textbook Luis Chapparo, Signals and Systems Using Matlab, 2 nd ed., Academic Press, 2015. Filters

More information

CS3291: Digital Signal Processing

CS3291: Digital Signal Processing CS39 Exam Jan 005 //08 /BMGC University of Manchester Department of Computer Science First Semester Year 3 Examination Paper CS39: Digital Signal Processing Date of Examination: January 005 Answer THREE

More information