ELE486: Digital Signal Processing

Department of Electrical Engineering
University of Southern Maine

Instructor: Mariusz Jankowski
Office: 127 John Mitchell Center
Telephone: (207) 780-5580
E-mail: mjankowski@usm.maine.edu

Course Description: Basic principles of processing digital signals. Sampling and quantization. Time and frequency domain representation and analysis of discrete-time signals and systems. FIR and IIR systems. Digital filter design; review of classic analog filter design (Butterworth, Chebychev). Finite-precision effects. Special topics may optimum linear filter theory, adaptive systems, signal compression and coding, DSP hardware.

Laboratories: This course is part of the "Integrating Mathematica into the electrical engineering curriculum" project. Included are a series of Mathematica notebooks. Students will be expected to use Mathematica to solve problems in class, as well as in take-home assignments and projects.

Course Objectives:
1. Introduce the theory of digital signal processing systems and applications and the mathematical tools that are fundamental to all DSP techniques.
2. Provide a thorough understanding and working knowledge of design, implementation and analysis of digital filters for processing of digital signals, and in their application to real signals (e.g., speech, images).

Course Outcomes:
A student completing this course should, at a minimum, be able to:
1. Determine properties of discrete-time systems such as linearity, stability, shift-invariance, and causality.
2. Model systems with difference equations and compute their solutions.
3. Visualize and compute discrete-time convolution and correlation.
4. Apply the z-transform as a tool in system modeling and analysis, and understand the related abstract concepts of a function of a complex variable and region of convergence.
5. Draw block diagrams of common digital filters
6. Demonstrate an understanding of the discrete-time Fourier transform and the concept of digital frequency.
7. Calculate, using a computer, the DFT of a signal.
8. Choose the sampling rate for a digital system and understand the effects of aliasing.
9. Design digital filters using bilinear transformation.
10. Design FIR filters using the window design method.


Prerequisites: ELE314, COS160 or equivalent. Lecture 3 hrs. 3 Cr.

Textbook: "Digital Signal Processing, a Computer-Based Approach," by Sanjit K. Mitra, McGraw Hill, Third Edition, 2006.

Week Topics Reading
1-2 Discrete-time signals and systems 1,2
3-4 Frequency-domain representation of signals 3.1-6
5 Z-transform representation of signals 3.7-11
6-7 Discrete-time systems in the transform domain 4
8-9 Digital processing of continuous-time signals 5
10 Digital filter structures 6.1-4
11-12 Digital filter design 7.1-9
13 DSP algorithms: FFT 8.3
14 Special topic


Grading policy: The final grade will be based on the results of several mid-semester exams, a final exam and computer projects or homework problems. These will be weighed equally, each part contributing approximately a third of your final grade.

Academic Support for Students with Disabilities - If you need course adaptations or accommodations because of a disability please contact the Office of Academic Support for Students with Disabilities, 237 Luther Bonney Hall, 780-4706, TTY 780-4395.