ECE 551 | Fall 2009

ECE 551, Fall 2009
Digital Signal Processing II

Course Staff

Pierre Moulin (Instructor)
moulin@ifp.uiuc.edu
Tel: 244-8366
Office hours: Wed 9:30-11 (+ by appointment, send me email)
Place: 2265 Beckman Institute

General Information

Pre-requisite:
ECE 410 (DSP I) and ECE 313 (Prob.) or equivalent.

Location: 218 MEB

Credit: 4 hours

Time table here

Lectures: Tue 3-4:50; Thu 3-3:50; Fri 2-3:20 (make-up)

Homeworks

HW1 (Solutions)
Assigned: 09/03, Due: 09/18

HW2 (Solutions)
Assigned: 09/23, Due: 10/12

HW3 (Solutions)
Assigned: 10/12, Due: 10/20

HW4: Do not turn in

HW5 (Solutions)
Assigned: 10/26, Due: 11/03

HW6 (Solutions)
Assigned: 11/09, Due: 11/19

HW7
Assigned: 11/21, Due: 12/04

Exams

Midterm 1 (Solutions)
10/22 (Thu) 7:30-9:30pm 243 MEB

Midterm 2 (Solutions)
11/05 (Thu) 2:30-3:50pm 218 MEB

Previous Exams

Midterm 1, Fall 2004

Notes

Course Notes by Prof. Andrew Singer

Notes on Multirate Signal Processing

Suggested Project Topics

Grading
HW + Matlab project (15%), two midterms (25% each) and a final (35%).

References

A.V. Oppenheim, R.W. Shafer, and J. R. Buck, Discrete-Time Signal Processing, Prentice-Hall, 1999.
A. C. Singer, Powerpoint Notes.
D. Jones, ECE451 Class Notes, 1995.
J.G. Proakis, C.M. Rader, F. Ling and C.L. Nikias, Advanced Digital Signal Processing, MacMillan, New York, 1992.
J.G. Proakis and D.G. Manolakis, Digital Signal Processing. Principles, Algorithms and Applications, 3rd Ed., Prentice-Hall, 1996.
T.W. Parks and C.S. Burrus, Digital Filter Design, Wiley, 1987.
Simon Haykin, Adaptive Filter Theory, 3rd Ed., Prentice-Hall, 199x.
P.P. Vaidyanathan, Multirate Systems and Filter Banks, Prentice-Hall, 1993.
M. Vetterli and J. Kovacevic, Wavelets and Subband Coding, Prentice-Hall, 1995.
J. H. McClellan, Computer-Based Exercises for Signal Processing using MATLAB 5.

Topics

Signals and Systems (~ 13 lectures)
- Fourier transform, sampling theory, LTI systems, filter structures, quantization effects, oversampled A/D converters
IIR filter design (~ 2 lectures)
- design from analog filters; least-squares digital filter design: Pade, Prony, Shanks; frequency-domain L^p optimization
FIR filter design (~ 4 lectures)
- window design, frequency sampling design, least-squares design, Parks-McClellan design; Chebyshev's alternation theorem; spectral factorization
Applications of FFT (2 lectures)
- Fast convolution algorithms, spectral analysis
Linear Prediction (3 lectures)
- AR modeling, lattice filters
System Identification/Modeling (~ 2 lectures)
- system identification based on FIR and IIR models; blind deconvolution; cepstral analysis
Adaptive Filters (~ 7 lectures)
- stochastic FIR Wiener filters; LMS algorithm; stability and performance; applications: adaptive equalizers, noise cancellation, echo cancellation, interference suppression; overview of advanced algorithms (RLS, etc.)
Multirate Signal Processing (~ 5 lectures)
- decimation and interpolation; sampling rate conversion; multistage implementation; subband coding; design of quadrature-mirror filters; wavelets; applications
Special Topics (if time permits)