ECE 445 Signal Processing
Technical Elective Course
Course Description (2009 Bulletin)
Study of signal conditioning, digital signal processing, and data processing. Topics
include transducers, high gain amplifier design, digital filtering, and spectrum estimation.
Specialized application determined by instructor. (3 Semester hours)
Proposed Revised Course Description
Selected topics in digital signal and image processing with design projects. The design
projects come from a variety of signal processing applications including medical image
processing, video processing, computer vision, statistical signal processing, speech
processing, radar signal processing, etc.
Prerequisites: ECE 334.
Class Schedule: 75-minute classes, twice weekly (Winter 2009)
Textbook
Chosen by the instructor, or replaced by instructor’s notes. Potential text selections
include:
T. Bose, Digital Signal and Image Processing, Wiley 2003.
A. Ambardar, Analog and Digital Signal Processing, PWS, 1995
References
Amos Gilat, MATLAB: An Introduction with Applications Third Edition, Wiley, 2007.
ISBN: 978-0-470-10877-2
W. J. Palm, Introduction to MATLAB 6 for Engineers, McGraw-Hill, 2001.
Engineering Tools
MATLAB, Simulink
Class Website
Isidore (access limited)
Goals
To provide a significant design experience in the area of signal processing and to provide
exposure to selected advanced topics in signal processing, including image processing.
Prerequisites by Topic
1. Continuous and discrete linear systems theory
2. MATLAB programming
Topics
This course covers selected advanced topics in signal processing. Topics build on the
prior course work, and lead to a significant design experience, either as one major design
project or several smaller design projects.
Topics may include:
1. Review of continuous and discrete transforms
2. Digital filter design
3. Adaptive filters
4. Wiener filters
5. Digital image processing and applications
6. Digital beam forming techniques
7. Parameter estimation techniques
8. Spectrum estimation
Assessment
Projects (50%), Midterm Test (25 %) Final Exam (25%) (Winter 2009)
Relevant ABET Program Outcomes
a
b
c
e
i
j
k
ability to apply knowledge of mathematics, science and engineering.
ability to design and conduct experiments, as well as to analyze and interpret data.
ability to design a system, component, or process to meet desired needs.
ability to identify, formulate, and solve engineering problems.
Our graduates will have a recognition of the need for, and an ability to engage in
life-long learning.
Our graduates will have knowledge of contemporary issues
able to use the techniques, skills, and modern engineering tools
Course Learning Outcomes
1. Students will understand continuous and discrete transforms as applied to signal
processing (a, e)
2. Students will be able to design digital filters to meet frequency selectivity
specifications (c, e)
3. Students will be able to do basic digital image processing using MATLAB (a, b, k)
4. Students will complete and document a major design experience in the area of signal
processing (a, b, c, e, i, j, k)
Prepared by: R. C. Hardie, Professor
Date: 12 November 2009