## 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: Prof. 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.

**GRADES:**

- Homework - 30%
- Midterm - 30%
- Final - 40%

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

- Design linear discrete-time systems and filters and analyze their behavior.
- Represent continuous-time signals and linear systems in discrete time, so that such signals can be recovered in continuous time when necessary.
- Compute approximations to Fourier transforms of continuous-time signals with finite discrete time methods.
- Take advanced courses in signal processing (image, speech, audio, etc.), communications, systems and control.

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