ece 429/529 digital signal processing robin n. strickland ece dept, university of arizona ECE 429/529 RNS

Transcription

1 ece 429/529 digital signal processing robin n. strickland ece dept, university of arizona 2007

2 SPRING 2007 SCHEDULE All dates are tentative. Lesson Day Date Learning outcomes to be Topics Textbook HW/PROJECT covered 1 W Jan 10 1 Introduction to DSP Chap. 1 2 F Jan Sequences, digital frequency , W Jan Sampling, aliasing 1.4 HW1 4 F Jan Quantization noise M Jan DT system components W Jan System properties 2.2 HW2 7 F Jan Filter realizations, impulse response M Jan Convolution 2.3 HW3 9 W Jan Correlation F Feb 2 21 (Forward) z-transform M Feb Time-shifting, DtFt existence, sequence type from ROC HW4 12 W Feb 7 24 (Inverse) z-transform F Feb 9 25 Applying z-transform properties M Feb Poles & stability, system analysis using z-transform 3.3, 3.6 REVIEW 15 W Feb 14 REVIEW REVIEW F Feb 16 EXAM 1 REVIEW 16 M Feb (Forward) Discrete-time Fourier transform (DtFt), symmetry PROJ 1 17 W Feb Frequency-shifting, modulation, filter design from lowpass prototypes F Feb Synthesis of filters using DtFt properties 4.3, M Feb DtFt analysis of downsampling, expansion, compression operations 4.3 HW5 20 W Feb DtFt systems analysis F Mar Phase and group delay of filters M Mar 5 42 Frequency response from poles & zeros 4.4 HW6 23 W Mar 7 43 Comb and notch filters F Mar 9 44 Minimum-phase filters M Mar Forward DFT and Inverse DFT, relationship to DtFt 5.1 PROJ 2 26 W Mar Applying DFT properties F Mar Convolution and correlation using DFT M Mar DFT symmetry, sinusoidal analysis and freq resolution 5.2 HW7 29 W Mar Zero-padding and windowing F Mar Spectral analysis M April 2 55 Mason s gain rule - REVIEW 32 W April 4 REVIEW REVIEW F April 6 EXAM 2 REVIEW 33 M April Filter architecture, filter comparisons, limit cycles , W April Linear phase FIR filter types F April FIR design by windowing 8.2 HW8 36 M April FIR design by windowing W April IIR filter design using bilinear transforms F April IIR filter design using bilinear transforms 8.3 HW9 39 M April DtFt analysis of sampling and aliasing W April Analog signal reconstruction, decimation and interpolation F April Digital audio applications of multirate DSP 10.9 REVIEW 42 M April 30 REVIEW REVIEW 42 W May 2 REVIEW Final Exam Wednesday, May 9, 11:00-1:00 p.m.

3 LESSON: 1 PAGE: 1 WHAT DOES ECE 429/529 COVER? Discrete-time signals & systems Discrete-time signals A/D & D/A conversion Convolution & correlation z-transform & Discrete-time Fourier transform Discrete-time systems Frequency response: gain, phase and group delay Digital filter principles: linear-phase filters, minimum-phase filters, notch filters, comb filters Multirate processing: decimation & interpolation Spectral analysis Discrete Fourier Transform (DFT) DFT properties, frequency resolution Fast convolution & correlation Zero-padding, spectral leakage, tapered windows Interpretation of DFT results Digital filter design Mason s gain rule Filter architectures FIR linear phase filters Window method of FIR design Analog filters basics IIR design using bilinear transform 50 db db digital frequency (rads) digital frequency (rads) Applications/simulations using MATLAB

4 LESSON: 1 PAGE: 2 DSP APPLICATIONS -Data acquisition -Spectral analysis -Simulation and modeling -Oil and mineral prospecting -Process monitoring & control -Nondestructive testing -CAD and design tools -Radar -Sonar -Ordnance guidance -Secure communication -Sound cards -Fax machines -Modems -Cellular phones -High-capacity hard disks -Digital TVs -Voice and data compression -Echo reduction -Signal multiplexing -Filtering -Digital audio recording and effects -Musical instruments -Image and sound compression for multimedia presentation -Movie special effects -Video conference calling -Diagnostic imaging (CT, MRI, ultrasound, and others) -Electrocardiogram analysis -Medical image storage/retrieval -Space photograph enhancement -Data compression e.g. JPEG, MPEG -Intelligent sensory analysis by remote space probes Example Listen to synthesized speech at Speech synthesis

5 LESSON: 1 PAGE: 3 HOW IS DSP DONE? Example Audio i/p Headphone o/p Laptop PC High level software e.g. MATLAB PC SOUND CARD C-code Crosscompiler

6 LESSON: 1 PAGE: 4 Describe the distinctions between analog, continuous-time, discrete-time and digital signals, and describe the basic operations involved in analog-digital (A/D) and digitalanalog (D/A) conversion.

7 LESSON: 1 PAGE: 5 TYPICAL DSP SYSTEM x(t) AAF SAMPLER x(nt) Q CODER x(n) DSP y(n) ZERO ORDER HOLD ARF y(t) ANALOG MIXED DIGITAL MIXED ANALOG AAF: anti-aliasing filter (analog), removes frequencies > F s /2 SAMPLER: effectively converts continuous-time t to discrete-time nt Q: B bits/sample quantizer, with 2 B levels CODER: produces byte stream DSP: digital signal processing algorithms ZOH: converts discrete samples to analog staircase waveform ARF: analog reconstruction (lowpass) filter, converts staircase to smooth waveform SIMPLIFIED DSP (DISCRETE-TIME) SYSTEM x(t) x(n) y(n) C/D DSP D/C y(t) T (sampling interval) T T F s = 1/T sampling interval (s) sampling frequency or sampling rate (Hz or samples/s)