ECE7251 Course Syllabus

ECE7251

Signal Detection and Estimation (3-0-3)

Technical Interest
Group

Digital Signal Processing

Prerequisites

ECE 6601

Corequisites

None

Catalog Description

Detection theory and estimation theory and their application to communications and statistical signal processing problems.

Textbook(s)

Hero, Notes for Class. (required) (comment: Notes from Al Hero of the University of Michigan will be used instead of a textbook)

Strategic
Performance
Indicators (SPIs)

SPIs are a subset of the abilities a student will be able to demonstrate upon successfully completing the course.

Topical Outline

Review of Stochastic Processes

Detection Theory
   Statistical Hypothesis Testing
   Hypothesis testing in additive Gaussian noise
   Hypothesis testing in the presence of unknowns
   Sequential hypothesis testing

Discrete-time Detection Theory
   Detection of known signals, unknown signals, and random signals
   Non-Gaussian detection
   Robust detection

Continuous-time Detection Theory
   Matched filter receivers
   Detection over complicated channels

Estimation Theory
   Estimation Theory Terminology
   Parameter Estimation
      Principles of parameter estimation
      Maximum likelihood estimation
      MAP estimation
      Least squares estimation
      Maximum entropy estimation
      Model order selection
   Signal Parameter Estimation
      Maximum likelihood estimation
      Prony's method
      Performance bounds
   Linear Signal Waveform Estimation
   Robust Estimation

Current Topics in Detection and Estimation (Specific topics will vary)
   Importance Sampling
   Distributed Detection
   Expectation/Maximization Algorithm
   High-order Statistical Analysis