Description
Springer Principles of Signal Detection and Parameter Estimation by Bernard C. Levy
This textbook provides a comprehensive and current understanding of signal detection and estimation, including problems and solutions for each chapter. Signal detection plays an important role in fields such as radar, sonar, digital communications, image processing, and failure detection. The book explores both Gaussian detection and detection of Markov chains, presenting a unified treatment of coding and modulation topics. Addresses asymptotic of tests with the theory of large deviations, and robust detection. This text is appropriate for students of Electrical Engineering in graduate courses in Signal Detection and Estimation._x000D_ Table of contents :- _x000D_
I Foundations.- Binary and Mary Hypothesis Testing.- Tests with Repeated Observations.- Parameter Estimation Theory.- Composite Hypothesis Testing.- Robust Detection.- II Gaussian 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.- III Markov Chain Detection.- Detection of Markov Chains with Known Parameters.- Detection of Markov Chains with Unknown Parameters._x000D_