University of Wisconsin Madison
Introduction to Random Signal Analysis and Statistics (E C E 331) Syllabus
Course Learning Outcomes
    Course Learning Outcome
  • 1
    Students should be able to do simple statistics and probability calculations.
  • 2
    They should be able to design a simple noise reduction filter.
Details
Introduction to Random Signal Analysis and Statistics
E C E 331 ( 3 Credits )
Description
Introduction to probability, random variables, and random processes. Confidence intervals, introduction to experimental design and hypothesis testing. Statistical averages, correlation, and spectral analysis for wide sense stationary processes. Random signals and noise in linear systems.
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
BUCKLEW, JAMES A
Text book, title, author, and year
Probability and Random Processes for Electrical and Computer Engineers; John Gubner; 1st; 2006
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. Axioms of Probability, Bayes Rule, Conditional Probabilities
  2. One Random Variables, PMF, CDF, PDF, and conditional versions Expectation and Conditional Expectation
  3. Many Random Variables, PMF, CDF, PDF, and conditional versions,
  4. Central Limit Theorem, confidence intervals
  5. Law of Large Numbers
  6. Stochastic Processes, Autocorrelation, Power Spectrum, Linear Systems
  7. Estimation and Filtering
Additional Information
 
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