ECE Digital Signal Processing

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1 University of Louisville Instructor:Professor Aly A. Farag Department of Electrical and Computer Engineering Spring 2006 ECE Digital Signal Processing Catalog Data: Office hours: Objectives: ECE 520: Digital Signal Processing. 3hrs Credits. Prerequisite: Signals & Linear Systems (ECE 420). Co-requisite: ECE 521.Discrete time signals and systems; Discrete Fourier Transforms, FFT algorithms, flow graph and the matrix representation of digital filters; FIR and IIR filter design techniques; quantization effects; spectral estimation; current applications of digital signal processing. Dr. Aly Farag (T, Th 4-5 p.m., and by appointment; Phone (502) , Rm 412 Lutz Hall); Hossam Abdelmunim, TA (M, W 2:30-3:30 p.m. and by appointment; Phone (502) , Rm 07 Lutz Hall) Course designed to provide students with foundations of discrete time signals and systems, as well as with FIR and IIR filter design techniques including computer methods for finding discrete Fourier Transforms. Course Learning Outcomes: 1. Study the representation of a periodic signal by Fourier series. 2. Calculate Fourier series coefficients using the all-familiar FFT algorithm. 3. Study the process of digitization of a continuous-time signal into a discrete-time sequence. 4. Study reconstruction of functions from its sampled version. 5. Compute the sequence Fourier transform of a sequence and correspond it with the continuous time Fourier transform, and examine the effect of changing the sampling rate. 6. Study the frequency response of common window functions. 7. Design a general purpose FIR digital filter based on the windowing method. 8. Evaluate an estimate of the power spectrum of a signal. 9. Study linear convolution using the FFT algorithm Textbook: References: 1. Class notes posted. 2. Oppenhium and Schafer Digital Signal Processing, 2'nd Edition, Prentice-Hall, New Jersey M. Smith and R. Mersereau, Introduction to Digital Signal Processing: A Computer Laboratory Textbook,John Wiley, New York, R. Mersereau and M. Smith, Digital Filtering: A Computer Laboratory Textbook, John Wiley, New York, J.H. McClellan, R.W. Schafer and M.A. Yoder, DSP First: A Multimedia Approach, Prentice Hall, New Jersey, L. B. Jackson, Digital Filters and Signal Processing, 2nd ed., Kluwer Academic Publishers, Boston, R. Kuc, Introduction to Digital Signal Processing, McGraw-Hill, New York, L. C. Ludeman, Fundamentals of Digital Signal Processing, Harper and Row, New York, J. Proakis and D. Manolakis, Introduction to Digital Signal Processing, Macmillan, New York, R. Roberts and C. Mullis, Digital Signal Processing, Addison-Wesley, Reading, MA, 1987.

2 9. R. Strum and D. Kirk, First Principles of Discrete Systems and Digital Signal Processing, Addison-Wesley, Reading, MA, L. R. Rabiner and B. Juang, Fundamentals of Speech Recognition, Prentice-Hall, New Jersey P. E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, New Jersey, R. Jimenez, Designing with Speech Processing Chips, Academic Press, New York, P. Strobach, Linear Prediction Theory, Springer-Verlag, New York, D. R. Brillinger, Time Series: Date Analysis and Theory, McGraw-Hill, New York, G. E. Box and G. M. Jenkins, Times Series Analysis: Forecasting and Control, Holden- Day, Oakland, CA, L. L. Scharf, Statistical Signal Processing, Addison Wesley, New York, B. Widrow and S. Stearns, Adaptive Signal Processing, Prentice-Hall, New Jersey, N. S. Jayant and P. Noll, Digital Coding of Waveforms, Prentice-Hall, New Jersey, Topics: I. AN OVERVIEW OF CONTINUOUS-TIME SIGNALS AND SYSTEMS (Notes-Chap. 1) I.1 Continuous-Time Systems I.2 Linear Systems I.3 Fourier Transforms I.4 Impulse Sampling II. DISCRETE-TIME SIGNALS AND SYSTEMS (Chap. 2) II.1 Sequences II.2 Discrete-Time Systems II.3 Linear Time-Invariant Systems II.4 Sequence Fourier Transform III. SAMPLING OF CONTINUOUS-TIME SIGNALS (Chap. 3) III.1 Periodic Sampling III.2 Frequency Domain Representation of Sampling III.3 Reconstruction of a Bandlimited Signal for its Samples III.4 Changing the Sampling Rate Using Discrete-Time Processing IV. THE Z-TRANSFORM (Chap. 4) IV.1 Definition of Z-transform IV.2 Region of Convergence of the Z-transform IV.3 The Inverse Z-Transform IV.4 Properties of the Z-Transform V. THE DISCRETE FOURIER TRANSFORM (Chap. 8) V.1 The Discrete Fourier Series V.2 Fourier Representation of Finite Duration Sequences V.3 The Discrete Fourier Transform V.4 Linear Convolution Using the Discrete Fourier Transform V.5 The Fast Fourier Transform (FFT) Algorithm(s) VI. TRANSFORM ANALYSIS OF LTI-SYSTEMS (Chap. 5) VI.1 Frequency Response of LTI Systems VI.2 System Functions for Systems VI.3 Frequency Response for Rational System Functions VII. STRUCTURES FOR DISCRETE-TIME SYSTEMS (Chap. 6) VII.1 Representation of Linear Constant-Coefficient Difference Equations VII.2 Basic Structures for IIR Systems VII.3 Basic Structures for FIR Systems VIII. FILTER DESIGN TECHNIQUES (Chap. 7) VIII.1 Design of Discrete-Time IIR Filters from Continuous-Time Filters VIII.2 Frequency Transformations of Lowpass IIR Filters VIII.3 Design of FIR Filters by Windowing VIII.4 Optimum Approximation of FIR Filters X. APPLICATIONS (Chap. 11, 12, and Notes) X.1 Classical and Modern Methods for Spectrum Estimation X.2 Homomorphic Deconvolution X.2 Speech Recognition

3 Class Policy: 1- Homework (15%), 2- Three one-hour exams (45%), 3- Comprehensive final exam (25%). 4- Projects (15%) AND 100% of ECE 521 Grade Grade A + A A - B + B B - C + C C - Range % A A< A - < B + < B < B - < C + < C < C - < 63

4 University of Louisville Instructor:Professor Aly A. Farag Department of Electrical and Computer Engineering Spring 2005 ECE Digital Signal Processing Catalog Data: Office hours: Objectives: ECE521: Digital Signal Processing Lab. 1hrs Credits. Prerequisite: Signals & Linear Systems (ECE 420). Co-requisite: ECE 520. Discrete time signals and systems; Discrete Fourier Transforms, FFT algorithms, flow graph and the matrix representation of digital filters; FIR and IIR filter design techniques; quantization effects; spectral estimation; current applications of digital signal processing. Dr. Aly Farag (T, Th 4-5 p.m., and by appointment; Phone (502) , Rm 412 Lutz Hall); Asem M Ali, TA (M, W 2:30-3:30 p.m. and by appointment; Phone (502) , Rm 06 Lutz Hall) Using the Matlab DSP, and signal/speech processing Toolboxes or other high level languages like C\C++. Calculate Fourier series coefficients using FFT algorithm. Finding discrete Fourier Transforms design FIR, and IIR filters. Evaluate an estimate of the power spectrum of a signal. Course Learning Outcomes: 1. Demonstrate the representation of a periodic signal by Fourier series. 2. Calculate Fourier series coefficients using the all-familiar FFT algorithm. 3. Reconstruct an approximation to the original periodic signal using only a portion of the Fourier series coefficients. 4. Get experience with available software tools (e.g. Matlab) for signal/speech processing. 5. Implement the process of digitization of a continuous-time signal into a discrete-time sequence. 6. Reconstruct the functions from its sampled version. 7. Compute the sequence Fourier transform of a sequence and correspond it with the continuous time Fourier transform, and examine the effect of changing the sampling rate. 8. Generate the frequency response of common window functions. 9. Design a general purpose FIR digital filter based on the windowing method. 10. Quantify the effects of windowing and spectral sampling associated with the DFT; 11. Evaluate an estimate of the power spectrum of a signal. 12. Implement linear convolution using the FFT algorithm 13. Experiment with elementary speech processing techniques. Textbook: 1. Class notes posted. 2. Oppenhium and Schafer Digital Signal Processing, 2'nd Edition, Prentice-Hall, New Jersey J. H. McClellan, C. S. Burrus, A. V. Oppenhium, T. W. Parks, R. W. Schafer, and H. W. Schuessler Computer-Based Exercises for Signal Processing Using Matlab Prentice-Hall, New Jersey References: 1. M. Smith and R. Mersereau, Introduction to Digital Signal Processing: A Computer Laboratory Textbook,John Wiley, New York, R. Mersereau and M. Smith, Digital Filtering: A Computer Laboratory Textbook, John Wiley, New York, 1994.

5 3. J.H. McClellan, R.W. Schafer and M.A. Yoder, DSP First: A Multimedia Approach, Prentice Hall, New Jersey, L. B. Jackson, Digital Filters and Signal Processing, 2nd ed., Kluwer Academic Publishers, Boston, R. Kuc, Introduction to Digital Signal Processing, McGraw-Hill, New York, L. C. Ludeman, Fundamentals of Digital Signal Processing, Harper and Row, New York, J. Proakis and D. Manolakis, Introduction to Digital Signal Processing, Macmillan, New York, R. Roberts and C. Mullis, Digital Signal Processing, Addison-Wesley, Reading, MA, R. Strum and D. Kirk, First Principles of Discrete Systems and Digital Signal Processing, Addison-Wesley, Reading, MA, L. R. Rabiner and B. Juang, Fundamentals of Speech Recognition, Prentice-Hall, New Jersey P. E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, New Jersey, R. Jimenez, Designing with Speech Processing Chips, Academic Press, New York, P. Strobach, Linear Prediction Theory, Springer-Verlag, New York, D. R. Brillinger, Time Series: Date Analysis and Theory, McGraw-Hill, New York, G. E. Box and G. M. Jenkins, Times Series Analysis: Forecasting and Control, Holden- Day, Oakland, CA, L. L. Scharf, Statistical Signal Processing, Addison Wesley, New York, B. Widrow and S. Stearns, Adaptive Signal Processing, Prentice-Hall, New Jersey, N. S. Jayant and P. Noll, Digital Coding of Waveforms, Prentice-Hall, New Jersey, Projects include: 1. Signal Representation, 2. Sampling, and Quantization, 3. Digital Filters Design, 4. Spectral Analysis, 5. Speech Analysis, 6. Wavelet Analysis, 7. Watermarking, and 8. Audio on the Web. Class Policy: Grade A + A A - B + B B - C + C C - Range % A A< A - < B + < B < B - < C + < C < C - < 63

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