COURSE TITLE: EECS 359 Digital Signal Processing

CATALOG DESCRIPTION: Discrete-time signals and systems, Discrete-Time Fourier Transform, z-Transform, Discrete Fourier Transform, Digital Filters.

REQUIRED TEXT: (Please note there is a new edition for Oppenheim and Schafer which will be available for purchase mid-summer) A.V. Oppenheim and R.W. Schafer, with J.R. Buck, Discrete-Time Signal Processing , Prentice Hall, 2 nd edition, 1999.

REFERENCE TEXTS: J.H. McClellan et al., Computer-Based Exercises for Signal Processing Using MATLAB 5 , Prentice Hall 1999.

COURSE COORDINATOR: Thrasyvoulos N. Pappas

COURSE GOALS: To provide a comprehensive treatment of the important issues in design, implementation, and application of digital signal processing algorithms.

PREREQUISITES: EECS 222

PREREQUISITES BY TOPIC:

1. Signals and linear systems theory

2. Laplace and Fourier transform

DETAILED COURSE TOPICS:

1. Discrete-time signals and systems. Linear Time-Invariant (LTI) Systems.

Linear constant-coefficient difference equations.

2. Frequency domain representation of discrete-time signals and systems.

The Discrete-time Fourier transform.

3. The z-transform, the inverse z-Transform, z-Transform properties.

4. Sampling of continuous-time signals. Sampling Theorem. Sampling Rate Conversions.

5. Transform analysis of linear time-invariant systems. The Frequency Response of LTI Systems.

Linear Systems with Generalized Linear Phase.

6. FIR and IIR filters. Structures for discrete-time systems.

7. Representation of Periodic and Finite-duration Sequences. The Discrete Fourier Series.

The discrete Fourier transform. Linear and Circular convolution.

8. Computation of the discrete Fourier transform. Decimation-In-Time and

Decimation-In-Frequency FFT Algorithms.

9. FIR and IIR filter design techniques.

COMPUTER USAGE: Students use MATLAB on a platform of their choice to do problems illustrating the above topics.

LABORATORY PROJECTS: See computer usage.

GRADES:

* Homework - 30%

* Midterm - 30%

* Final - 40%

COURSE OBJECTIVES: When a student completes this course, s/he should be able to:

1. Design linear discrete-time systems and filters and analyze their behavior.

2. Represent continuous-time signals and linear systems in discrete time, so that such signals can be recovered in continuous time when necessary.

3. Compute approximations to Fourier transforms of continuous-time signals with finite discrete time methods.

4. Take advanced courses in signal processing (image, speech, audio, etc.), communications, systems and control.

ABET CONTENT CATEGORY: 100% Engineering (Design component).