1. Alpha
Course Title
Credits
ETRO Number
Signal Processing
3
450
Department
Date of Outline
STEM Author Dr. Jung Park
09/10/2010 Effective Date Fall 2011 5-year Review Date spring 2016
2. Course Description: Introduces digital signal processing, discrete-time signals and systems, z-transform, linear shift-invariant systems, discrete Fourier transform (DFT) and fast Fourier transform
(FFT) algorithms, and design of digital filters. Provides laboratory hands-on applications of concepts and theories.
Cross-list
Contact Hours/Type 3 hr. lecture
3. Pre-requisites ETRO 360 with grade C or better.
Pre-requisite may be waived by consent yes no
Co-requisites
Recommended Preparation
4. Function/Designation AA Category Additional Category
AS Program Category List Additional Programs and Category:
AAS Program Category
BAS Program Other
List Additional Programs and Category:
List Additional Programs and Category: Engineering Technology
Developmental/Remedial Other/Additional: Explain:
See Curriculum Action Request (CAR) form for the college-wide general education student learning outcomes (SLOs) and/or the program learning outcomes (PLOs) this course supports.
______________________________________________________
Chancellor
Revised 4/13/2020
______________________
Approval Date
Course Outline, page 1

This course outline is standardized and/or the result of a community college or system-wide agreement.
Responsible committee:
2
5. Student Learning Outcomes (SLOs): List one to four inclusive SLOs.
For assessment, link these to #7 Recommended Course Content, and #9 Recommended Course
Requirements & Evaluation. Use roman numerals (I., II., III.) to designate SLOs
On successful completion of this course, students will be able to:
I. utilize basic concepts of discrete-time signal processing and systems;
II. analyze advanced signal processing technologies;
III. solve the problems related to analysis of discret-time signals and systems and compute the system output; and
IV. use software such as MATLAB to represent digital signals and systems and to compute the system output.
6. Competencies/Concepts/Issues/Skills
For assessment, link these to #7 Recommended Course Content, and #9 Recommended Course
Requirements & Evaluation. Use lower case letters (a., b.…zz. )to designate competencies/skills/issues
On successful completion of this course, students will be able to: a. determine whether systems are linear or nonlinear, causal or noncausal, shift-invariant, or shift varying; b. model systems with difference equations and compute their solutions; c. visualize and compute discrete-time convolution; d. determine unit-pulse response and convolution using the concept of transfer function; e. demonstrate an understanding of the discrete-time Fourier transform and the concept of digital frequency; f. choose the sampling rate for a digital system and understand the effects of aliasing; g. determine the discrete Fourier transform (DFT) of an aperiodic sequence; h. draw signal flow graphs respresenting the computation stages in the decimation-in-time and decimation-in-frequency FFT algorithms; i. convert an analog lowpass filter into an equivalent digital filter; j. demonstrate knowledge of parameter quantization effects; and k. utilize MATLAB programs to process filter sequences and display results.
7. Suggested Course Content and Approximate Time Spent on Each Topic
Linked to #5. Student Learning Outcomes and # 6 Competencies/Skills/Issues
Overview of signals and systems. 1-2 weeks (I, IV, a, b, k)
Discrete signals, discrete systems, unit sample response, discrete convolution. 3-4 weeks (I, II, III, IV, a, b, c, d, k)
Discrete time Fourier transform, z-transform. 3-4 weeks (I, II, III, IV, b, c, d, e, f, k)
Discrete Fourier Transform (DFT). 3-4 weeks (I, II, III, IV, b, c, e, f, g, k)
Fast Fourier Transform (FFT) algorithms. 3-4 weeks (I, II, III, IV, b, c, e, f, g, h, k)
Digital filter design. 3-4 weeks (I, II, III, IV, b, c, e, f, g, h, i, j, k)
Realization of digital filters: applications of digital signal processing. 3-4 weeks (I, II, III, IV, b, c, e, f, g, h, i, j, k)
Revised 4/13/2020 course outline

8. Text and Materials, Reference Materials, and Auxiliary Materials
3
Appropriate text(s) and materials will be chosen at the time the course is offered from those currently available in the field. Examples include:
A. V. Oppenheim and R. W. Schafer, Digital Signal Processing, 1/E, Prentice Hall Publishers, 1975,
ISBN 0-132-14635-5
Appropriate reference materials will be chosen at the time the course is offered from those currently available in the field. Examples include:
S. K. Mitra, Digital Signal Processing, 3rd, McGraw Hill, 2006, ISBN-10: 0072865466
J. G. Proakis, O. G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, 4th,
Prentice-Hall, 2007.
Appropriate auxiliary materials will be chosen at the time the course is offered from those currently available in the field. Examples include: software such as MATLAB
9. Suggested Course Requirements and Evaluation
Linked to #5. Student Learning Outcomes (SLOs) and #6 Competencies/Skills/Issues
Specific course requirements are at the discretion of the instructor at the time the course is being offered.
Suggested requirements might include, but are not limited to: labs/exercises: 40-60% (I, II, III, IV, a-k) class participation: 5-10% (I, II, III, IV, a-k) projects/research: 10-20% (I, II, III, IV, a-k) quizzes (In class & pre-class): 10-20% (I, II, III, IV, a-k) written examinations: 10-30% (I, II, III, IV, a-k)
10. Methods of Instruction
Instructional methods will vary considerably by instructor. Specific methods are at the discretion of the instructor teaching the course and might include, but are not limited to: inquiry lab experiences; lab activities and exercises; demonstrations; group projects or team challenges; audio/visual presentations (pre-prepared or internet-based); class discussions; guest speakers or field trips; and lectures.
11. Assessment of Intended Student Learning Outcomes Standards Grid attached
12. Additional Information:
Revised 4/13/2020 course outline