Signal Detection and Estimation

(3-0-0-3)

CMPE Degree: This course is Not Applicable for the CMPE degree.

EE Degree: This course is Not Applicable for the EE degree.

Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.

Technical Interest Group(s) / Course Type(s): Digital Signal Processing

Course Coordinator:

Prerequisites: ECE 6601

Corequisites: None.

Catalog Description

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

Textbook(s)

Notes for Class

Course Outcomes

Not Applicable

Student Outcomes

In the parentheses for each Student Outcome:
"P" for primary indicates the outcome is a major focus of the entire course.
“M” for moderate indicates the outcome is the focus of at least one component of the course, but not majority of course material.
“LN” for “little to none” indicates that the course does not contribute significantly to this outcome.

1. ( Not Applicable ) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics

2. ( Not Applicable ) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors

3. ( Not Applicable ) An ability to communicate effectively with a range of audiences

4. ( Not Applicable ) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts

5. ( Not Applicable ) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives

6. ( Not Applicable ) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions

7. ( Not Applicable ) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Strategic Performance Indicators (SPIs)

Not Applicable

Course Objectives

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