Principles of Signal Detection and Parameter Estimation
Levy, Bernard C.
2008, 664 p. 101 illus.
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Treats both Gaussian detection and the detection of Markov chains
Covers the asymptotic of tests with the theory of large deviations
Presents aspects of both Bayesian and frequentist detection
Addresses robust detection
Includes problems and solutions for each chapter
Provides a comprehensive and current understanding of signal detection and estimation
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.
Content Level »Graduate
Keywords »Modulation - communication - hidden markov models - hypothesis testing - markov - models - radar signal processing