EECS 251A Detection, Estimation, and Demodulation Theory (2013-2014)

EECS 251A Detection, Estimation, and Demodulation Theory

(Not required for any major.)
Catalog Data:

EECS 251A Detection, Estimation, and Demodulation Theory (Credit Units: 4) Fundamentals of hypothesis testing and Bayes and Maximum Likelihood Estimation. ARMA and state variable models for random time series analysis. Wiener and Kalman filtering and prediction. Adaptive algorithms for identification and tracking of parameters of time-varying models. Prerequisite: EECS240. (Design units: 0)

Required Textbook:
. Edition, , 1969, ISBN-13 978-0201361865.

Recommended Textbook:
None
References:
None
Coordinator:
Relationship to Student Outcomes
No student outcomes specified.
Course Learning Outcomes. Students will:
Prerequisites by Topic
Lecture Topics:

None.

Class Schedule:

Meets for 3 hours of lecture each week for 10 weeks.

Computer Usage:
Laboratory Projects:
Professional Component
Design Content Description
Approach:
Lectures:
Laboratory Portion:
Grading Criteria:
Estimated ABET Category Content:

Mathematics and Basic Science: 0.0 credit units

Computing: 0.0 credit units

Engineering Topics: 0.0 credit units

Engineering Science: 0.0 credit units

Engineering Design: 0.0 credit units

Prepared:
July 11, 2012
Senate Approved:
February 2, 2012
Approved Effective:
2012 Fall Qtr