Digital Signal Processing

Tentative Schedule

(more information will be made available here over time)

Course Notes Signal Processing Toolbox (For Use With Matlab)

Date
Major topic
Keywords
Section textbook
Homework/Projects/
Handouts
Aug.  28 (T)
1. Introduction
  • History, analog vs. digital
  • Digital signal processors
  • Prerequisites: discrete time signals and systems, DFT, z-transform, frequency analysis of signals and systems
1-5

Aug. 30 (R)
2. Sampling and reconstruction of signals

  • Ideal (periodic) sampling, frequency domain representation of sampling, nonideal sampling, aliasing
  • Nyquist (sampling) theorem
  • Sampling of bandpass signals
  • Reconstruction, sinc-interpolation
  • Discrete-time processing of continuous-time signals
  • Antialiasing filtering, A/D conversion, sample&hold
  • Quantization, quantization errors
  • D/A conversion, sample&hold
  • A/D and D/A converter realizations
6.1-6.5


Sep. 04 (T)
Homework 1,
Solution 1
Sept. 04 (R)

Sep. 6 (T)
3. Implementation of discrete-time systems
  • Structures for FIR systems (direct-form, cascade-form, lattice structures)
  • Structures for IIR systems (direct-form, cascade-form, parallel-form)
  • Coefficient quantization and round-off effects (fixed-point number representations, round-off noise, limit cycles)
9.1-9.6

Sep. 11 (R)
Homework 2
Sep. 13 (T)

Sep. 18 (R)
Sep. 20 (T)
4. Design of digital filters
  • Linear-phase filters
  • FIR design: window-based design, frequency-sampling design, Chebyshev aproximation
  • IIR design via bilinear and impulse-invariant transform

10.1-10.3
Project 1 usound110.m
usound441.m
projIA.mat
projIB.mat
Sep. 25 (R)

equalizer.m
Sep. 27 (T)

Homework 3
Oct. 2 (R)
5. Multirate digital signal processing

  • Downsampling and upsampling
  • Polyphase decomposition
  • Nyquist-filters
  • Sampling-rate conversion
  • Efficient multirate filtering

 

11.1-11.12


Oct. 4 (T)
Homework 4
Oct. 9 (R)

Oct. 11 (T) Homework 5
Oct. 16 (R)
midterm exam



Oct. 18 (T)
5. Multirate digital signal processing
  • Oversampled A/D and D/A conversion
  • Two-channel QMF and perfect reconstruction filter banks
  • Modulated filter banks

11.1-11.12



Nov. 6 (R)
Homework 6
Nov. 8 (Mo)
Project2 (Literature)
Nov. 13 (R) 6. Power spectrum estimation
  • Nonparametric (classical) methods: periodogram, Bartlett method, Welch method, Blackman-Tukey method
  • Parametric methods: Yule-Walker method
  • AR, MA, ARMA processes
14.1-14.3

Nov. 15 (Fr)

Nov. 20 (T) Homework 7
Nov. 22 (R)

Nov. 27 (T)
Homework 8
Nov. 29 (T)
Project presentation seminar: Wavelet transform and applications








Dec. 4 (R)

Dec. 4 (Fr)

Dec. 6 (T)
6. Power spectrum estimation
  • MA estimation, Durbin's method
14.1-14.3
Dec. 11 (R)
Final exam









Online Resources



Online demos (DSP, Signals and Systems):
Online lectures and classnotes:



1. Introduction   To schedule


2. Sampling of continuous-time signals, reconstruction To schedule


3. Implementation of discrete-time systems
To schedule


4. Design of digital filters
To schedule


5. Multirate digital signal processing To schedule


6. Spectral estimation
To schedule




A. ZAIDI, 08/24/2007