University of Wisconsin Madison
Digital Signal Processing Laboratory (E C E 432) Syllabus
Course Learning Outcomes
    Course Learning Outcome
  • 1
    Students will be able to design fixed-coefficient IIR (infinite impulse response) and FIR (finite impulse response) digital filters to performance specifications for pass band, stop band, roll off and computational efficiency.
  • 2
    Students will be able to write a computer software module implementing a digital filter in an algorithmic and object-oriented language such as Java or C++. Write such a module to an interface specification that allows that module to be incorporated into a larger software system.
  • 3
    Test such a computer software module for conformance to specification and correctness.
  • 4
    Students will be able to develop specifications, design, implement, and test digital filters as part of the solution of an engineering problem.
Digital Signal Processing Laboratory
E C E 432 ( 3 Credits )
Implementation of digital signal processing algorithms on special-purpose and general-purpose hardware. Use of assembly and high-level languages, and simulator to develop and test IIR, FIR filters and the FFT for modern DSP chips. Scaling for fixed point arithmetic. Use of high level languages to implement real time, object oriented component based DSP systems in general purpose computers. DSP applications, including data and voice communication systems.
ECE 431, Comp Sci 302
College: College of Engineering
Instructor Name
Instructor Campus Address
Contact Hours
Course Coordinator
Text book, title, author, and year
Supplemental Materials
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. Coupled-oscillator filters and waveform generators.
  2. Realization of filters in software modules, testing of such software modules.
  3. Bi-linear transform design of IIR (infinite impulse response) filters, the digital
  4. Butterworth filter.
  5. Principles of digital spectrum analysis, interpreting effect of rectangular and Hamming
  6. window on the output of digital spectrum analyzers.
  7. Window-design FIR (finite impulse response) filters.
  8. Frequency sample-design FIR filters.
  9. Implementation of FIR filters using IIR structures.
  10. Application of digital filters in analog communication systems.
  11. Design of digital matched filters for digital communication systems.
  12. Filter trees and their application in sub band coding.
Additional Information
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