University of Wisconsin Madison
Digital Signal Processing (E C E 431) Syllabus
Course Learning Outcomes
    Course Learning Outcome
  • 1
    Students will use the DFT to perform spectral analysis of signals.
  • 2
    Students will be able to design frequency selective IIR filters.
  • 3
    Students will be able to design arbitrary FIR filters
  • 4
    Students will be able to perform signal processing operations using MATLAB.
  • 5
    Students will be able to relate the poles and zeros of a discrete-time system to the frequency response.
  • 6
    Students will be able to choose anti-aliasing and anti-imaging filter characteristics, and appropriate sampling rates for converting a continuous-time signal to discrete time and vice versa.
Details
Digital Signal Processing
E C E 431 ( 3 Credits )
Description
Sampling continuous-time signals and reconstruction of continuous-time signals from samples; spectral analysis of signals using the discrete Fourier transform; the fast Fourier transform and fast convolution methods; z-transforms; finite and infinite impulse response filter design techniques; signal flow graphs and introduction to filter implementation.
Prerequisite(s)
ECE 330
Department: ELECTRICAL AND COMPUTER ENGR
College: College of Engineering
Instructor
Instructor Name
Instructor Campus Address
instructorEmail@emailaddress.edu
Contact Hours
4.0
Course Coordinator
Barry Van Veen
Text book, title, author, and year
Discrete-Time Signal Processing; Oppenheim; third; 2010
Supplemental Materials
None
Required / Elective / Selected Elective
Selected Elective
ABET Program Outcomes Associated with this Course
Program Specific Student Outcomes
 
Brief List of Topics to be Covered
  1. Discrete-time signals and systems; Time series; The linear time shift invariant system and convolution; Bounded input-bounded output stability.
  2.     The z-transform; Forward z-transform; Inverse z-transform; Causal and noncausal signals.
  3.     Input/output relationships; Transfer functions and frequency response; Difference equations.
  4.     Filter networks; Signal flow graphs.
  5.     Sampling; Relationship between continuous and discrete time domains; Anti-alias filters, A/D, D/A conversion.
  6.     Discrete Fourier Transform; Fourier transform relationships and properties; Windowing; FFT algorithm.
  7.     IIR filter design; Pole transformation; Impulse invariance; Bilinear z transformation.
  8. FIR filter design; Window method; Frequency sampling method.
Additional Information
 
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