Instructor:
Reza Soleymani; Lecture:
Monday 2:45PM - 5:30PM in LS 210; Office:
EV005.125; Office Hours: Tuesdays:
13h-14h; Phone: 4103; Email: msoleyma@ece.concordia.ca
This
course focuses on fundamental concepts, algorithms, and applications of digital
signal processing (DSP). The purpose is to enable you to apply DSP theory and
methods to solve basic engineering problems.
Description: “Review of Z-transform; linear phase and non-linear
phase systems; all-pass and minimum phase systems, recursive and non-recursive
digital filters; common digital filter structures, common design approaches for
digital filters; description of typical Digital Signal Processor chips; review
of sampling, reconstruction, interpolation and decimation; changing the
sampling rate by integer and non-integer factor; multirate
signal processing, polyphase decomposition, multirate filter banks; digital processing of analog
signals, A/D and D/A converters; discrete Fourier transform; random signals,
Least-Mean-Square (LMS) filters. Lectures: three hours per week. Laboratory: 15
hours total. Prerequisite: ELEC 342
or 364; ENGR 371.”
Text: Digital Signal Processing, 4th Edition, John G. Proakis, and Dimitris K Manolakis,
4th edition, Pearson, 2007.
Grading:
|
Labs |
20% |
|
Assignments |
10% |
|
Midterm |
20% |
|
Final |
50% |
Midterm Date: March 8, 2020,
3:00 PM - 5:00 PM, Room: MB S2.210
Exams: Exams
are closed books but formulas sheets are permitted (1 sheet – 2 sided)
Not to write the midterm exam (except for
medical emergencies) results in loss of the 20% assigned to it.
Assignments: A set of problems based on
the textbook will be given. The suggested problems provide hands on experience
with the theoretical concepts. They also are the best indicator of what you
should expect in the midterm and the final exams. There is no substitute for
you sitting down and trying these on your own. Out of the suggested problems,
there will be 4 assignments, to submit in the mailbox of the instructor.
Labs: There are five labs, provided to help you get better understanding of
the theoretical concepts and DSP methods learnt in class and gain hands-on
experience of the application of signal processing algorithms. Your lab report
will be due approximately two weeks after the Friday on which you are supposed
to do the lab. The passing grade in the lab portion required to pass the course
is 60%.
For further details see: https://users.encs.concordia.ca/~pbipin/ELEC442/index442.html
You need to submit only one signed "Expectations of
originality form" for all the work.
LECTURE NOTES: Solution to Suggeted
Problems.htm
Course Schedule:
|
Topic |
Chapter/notes |
Description |
Suggested problems |
Assignments |
|
Discrete-Time (DT) Signals
and Systems: |
Sections 2.1-2.5, Week 1 |
DT signals, linear
time-invariant (LTI) systems, stability and causality, discrete convolution,
linear constant coefficient difference equation. |
2.1, 2.3, 2.6, 2.8, 2.15,
2.17, 2.31, 2.37, 2.38, 2.49, 2.51, 2.58, |
|
|
Z-Transform |
Sections 3.1-3.6, Week 2 |
Definition and properties
of z-transform, region of convergence, inverse z-transform, system function of LTI systems. |
3.1, 3.2, 3.3, 3.6, 3.10,
3.11, 3.14a, 3.14g, 3.16a, 3.19, 3.25, 3.36, 3.38a, 3.38c, 3.43 |
2.18, 2.35, 2.48, 2.49, 3.1, 3.25, 3.34, 3.37 Due: Jan. 27, 2020 |
|
Sampling of Continuous-Time
(CT) Signals |
Sections 6.1-6.5, Week 3 |
Sampling of CT signals,
effect of sampling in frequency domain, Nyquist theorem, reconstruction of CT
signals, digital processing of CT signals, change of sampling rate,
decimation and interpolation, A/D and D/A conversions. |
6.1, 6.3, 6.9, 6.10, 6.15,
6.18,
|
|
|
DFT and FFT |
Sections 7.1, 7.2, 7.4, 8.1 Week 4 |
Discrete Fourier Transform
(DFT), Properties of DFT, Frequency domain analysis of LTI systems using DFT, Efficient Computation of
DFT. |
7.13, 7.17, 7.18, 7.22,
7.23b,7.23f, 7.24, 8.8, 8.11 |
Assignment 2: 6.11, 6.18, 7.2a, 7.2b, 7.8, 8.11 Due: Feb. 17, 2020 |
|
Implementation of DT
Systems |
Sections 9.1-9.6 Weeks 5 and 6 |
Structure for FIR and IIR
Systems, Filter Coefficient Quantization, Round-Off Effect in Digital
Filters. |
9.1, 9.2, 9.4, 9.6, 9.7,
9.9a, 9.10, 9.15, 9.16, 9.18, 9.35, 9.38 |
Assignment 3: 9.2, 9.3, 9.8, 9.35, 9.38 Due: March 2, 2020 |
|
Filter Design Techniques |
Sections 10.1-10.4 Weeks 7, 8 |
Specifications of digital
filters, design of IIR filters, bilinear transform, design of FIR filters
using window functions and optimization. |
10.1, 10.5, 10.7, 10.8,
10.10, 10.12, 10.14, 10.16, 10.20, 10.22, 10.25 |
Assignment 4: 10.1, 10.5, 10.10, 10.13, 10.16, 10.21 (a and b)
Due: March 30, 2020 |
|
Multirate Digital Signal Processing |
Sections 11.1-11.5. Week 9 |
Decimation, Interpolation,
Rational rate conversion, Polyphase Filters. |
11.1, 11.2. 11.5, 11.6,
11.9, 11.10, 11,11, 11.28, 11.29 |
Assignment 5: 11.1, 11.5, 11.13 Due: April 6, 2020 |
|
Linear Prediction |
Sections 12.1-12.4, 12.7 Week 10-11 |
Review of Random Processes,
Forward Linear Prediction, Levinson-Durbin Algorithm, FIR Wiener Filter |
12.1,
12.2, 12.3, 12.14, 12.19, 12.32, |
|
|
Adaptive Systems |
13.1-13.3 Week 12 |
Applications of the
Adaptive Filters, LMS Algorithm, RLS Algorithm |
13.1,
13.2, 13.12, 13.16, 13.18, |
|