Principles of Signal Detection and Parameter Estimation
Autor Bernard C. Levyen Limba Engleză Paperback – 5 noi 2010
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Specificații
ISBN-13: 9781441945655
ISBN-10: 1441945652
Pagini: 660
Ilustrații: 664 p. 101 illus.
Dimensiuni: 155 x 235 x 35 mm
Greutate: 0.91 kg
Ediția:Softcover reprint of hardcover 1st ed. 2008
Editura: Springer Us
Colecția Springer
Locul publicării:New York, NY, United States
ISBN-10: 1441945652
Pagini: 660
Ilustrații: 664 p. 101 illus.
Dimensiuni: 155 x 235 x 35 mm
Greutate: 0.91 kg
Ediția:Softcover reprint of hardcover 1st ed. 2008
Editura: Springer Us
Colecția Springer
Locul publicării:New York, NY, United States
Public țintă
GraduateCuprins
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.
Textul de pe ultima copertă
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.
Caracteristici
For graduate EE courses on Detection and Estimation Theory Modern classical communications theory approach Includes both analog and digital communication New developments such as detection of Markov Chains, Gaussian and Robust detection, sequential testing, etc. Problems, Solutions Manual Includes supplementary material: sn.pub/extras Request lecturer material: sn.pub/lecturer-material