# The Department of Electrical Engineering & Computer Science

## 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: A.V. Oppenheim and R.W. Schafer, Discrete-Time Signal Processing , Prentice Hall, 3rd edition.

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:

Discrete-time signals and systems. Linear Time-Invariant (LTI) Systems.
Linear constant-coefficient difference equations.
Frequency domain representation of discrete-time signals and systems.
The Discrete-time Fourier transform.
The z-transform, the inverse z-Transform, z-Transform properties.
Sampling of continuous-time signals. Sampling Theorem.
Sampling Rate Conversions.
Transform analysis of linear time-invariant systems.
The Frequency Response of LTI Systems.
Linear Systems with Generalized Linear Phase.
FIR and IIR filters. Structures for discrete-time systems.
Representation of Periodic and Finite-duration Sequences.
The Discrete Fourier Series.
The discrete Fourier transform.
Linear and Circular convolution.
Computation of the discrete Fourier transform.
Decimation-In-Time and Decimation-In-Frequency FFT Algorithms.
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.

• 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).

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