This new textbook is for contemporary signal detection and parameter estimation courses offered at the advanced undergraduate and graduate levels. It presents a unified treatment of detection problems arising in radar/sonar signal processing and modern digital communication systems. The material is comprehensive in scope and addresses signal processing and communication applications with an emphasis on fundamental principles. In addition to standard topics normally covered in such a course, the author incorporates recent advances, such as the asymptotic performance of detectors, sequential detection, generalized likelihood ratio tests (GLRTs), robust detection, the detection of Gaussian signals in noise, the expectation maximization algorithm, and the detection of Markov chain signals. Numerous examples and detailed derivations along with homework problems following each chapter are included.
|Edition description:||Softcover reprint of hardcover 1st ed. 2008|
|Product dimensions:||6.00(w) x 8.90(h) x 1.00(d)|
Table of Contents
Introduction.- Binary and M-ary Hypothesis Testing.- Tests with Repeated Observations.- Parameter Estimation Theory.- Composite Hypothesis Testing.- Robust Detection.- Karhunen-Loeve Expansion of Gaussian Processes.- Detection of Known Signals in Gaussian Noise.- Detection of Signals with Unknown Parameters.- Detection of Gaussian Signals in WGN.- EM Estimation and Detection of Gaussian Signals with Unknown Parameters.- Detection of Markov Chains with Known Parameters.- Detection of Markov Chains with Unknown Parameters.