ECE 6723 Detection and Estimation Theory 3.0 Credits
This course introduces the field of detection and estimation and provides tools for classifying and learning about patterns in the face of total, partial or incomplete prior knowledge. Topics covered include Bayes classifier; Parametric estimation and supervised learning (MLE and Bayes Learning); Hypothesis testing; Decision Fusion; Unsupervised learning; and Non parametric testing.
Repeat Status: Not repeatable for credit
Prerequisites: ECE 5700 [Min Grade: C] or ECES 521 [Min Grade: C]