Course Description and Prerequisites
EE 421G provides an introduction to continuous and discrete signal and system models and analyses. Topics include discrete and continuous convolution, Fourier series, Fourier transforms, and Laplace and Z-transforms with application examples including AM modulation and the sampling theorem. The course draws on applied calculus to present signals and systems concepts, with connections to real-world image and signal processing applications. Prerequisites: MA 214 and a “C” or better in EE 221; corequisite MA 320. Learning Outcomes
Upon completion, students should demonstrate the ability to:
Signals and Systems, 2nd Ed., A. V. Oppenheim and A. S. Willsky, Prentice Hall, 1997. Supplemented with Calculus, 5th Ed., J. Stewart, Thomson Learning, 2003. Course Topics
EE 421G provides an introduction to continuous and discrete signal and system models and analyses. Topics include discrete and continuous convolution, Fourier series, Fourier transforms, and Laplace and Z-transforms with application examples including AM modulation and the sampling theorem. The course draws on applied calculus to present signals and systems concepts, with connections to real-world image and signal processing applications. Prerequisites: MA 214 and a “C” or better in EE 221; corequisite MA 320. Learning Outcomes
Upon completion, students should demonstrate the ability to:
- Classify systems based on input-output relationships (linearity, time-invariance)
- Understand the relationship between sampling rate and aliasing errors
- Analyze and synthesize signals using Fourier series and transform definitions
- Analyze practical continuous-time and discrete-time systems (modulators, filters)
- Analyze systems with Laplace and Z-transforms
- Characterize LTI systems using impulse response and transfer function representations
- Apply convolution to determine the output of LTI systems
Signals and Systems, 2nd Ed., A. V. Oppenheim and A. S. Willsky, Prentice Hall, 1997. Supplemented with Calculus, 5th Ed., J. Stewart, Thomson Learning, 2003. Course Topics
- Continuous and discrete time signals
- Linear time-invariant (LTI) systems
- Continuous and discrete time Fourier transforms
- Laplace and Z-transforms
- Discrete filter design
- Homework assignments (10%)
- Web abstracts on signal/image processing topics (10%)
- Practice quizzes (5%)
- Three semester exams (15% each)
- Comprehensive final exam (30%)
| Semester | Materials |
|---|---|
| Fall 2010 | Syllabus, Simulink models, programming assignments, exam results |
| Fall 2011 | Syllabus, three volumes of lecture notes (Keynote/PPT), exams (3 semester + final), quizzes (3), Simulink models, project report template |
| Fall 2012 | Three semester exams + final, quiz, circuit diagrams |
| Fall 2013 | Syllabus, three volumes of student lecture notes, homework, lectures PDF, exams (3 semester + final), quiz |
| Fall 2014 | Syllabus, three volumes of notes, four exams (versions A and B), class roster |
| Spring 2017 | Four exams (with makeup versions), supplemental chapter notes (Ch. 5–10), team assignments, skills assessment, project evaluation guide |
