COURSE
TITLE: ECE 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, with J.R. Buck, Discrete-Time Signal Processing,
Prentice Hall, 2nd 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: ECE 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).