Introduction to Signal Estimation and Detection Theory

This series of six lessons introduces you to the principles of signal estimation and signal detection or hypothesis testing. You will the maximum likelihood criterion for estimation and how to classify different types of hypothesis tests and the metrics used to characterize the performance of detectors such as the probability of correct detection and the receiver operating characteristic or ROC. You will learn about the likelihood ratio, which is the optimal test of simple binary hypotheses. There are no known optimal tests for more general testing scenarios, so you will learn about the generalized likelihood ratio as a principled approach for obtaining a good test.