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Robust and Distributed Hypothesis Testing

Gökhan Gül (Autor)

Buch | Hardcover

XXI, 141 Seiten

2017 | 1st ed. 2017
Springer International Publishing (Verlag)
978-3-319-49285-8 (ISBN)

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This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the book describes the derivation of theoretical bounds in minimax decentralized hypothesis testing, which have not yet been known. As a timely report on the state-of-the-art in robust hypothesis testing, this book is mainly intended for postgraduates and researchers in the field of electrical and electronic engineering, statistics and applied probability. Moreover, it may be of interest for students and researchers working in the field of classification, pattern recognition and cognitive radio.

Introduction.- Background.- Robust Hypothesis Testing with a Single Distance.- Robust Hypothesis Testing with Multiple Distances.- Robust Hypothesis Testing with Repeated Observations.- Robust Decentralized Hypothesis Testing.- Minimax Decentralized Hypothesis Testing.- Conclusions and Outlook.

Erscheinungsdatum	04.04.2017
Reihe/Serie	Lecture Notes in Electrical Engineering
Zusatzinfo	XXI, 141 p. 47 illus., 42 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Technik ► Elektrotechnik / Energietechnik
Schlagworte	classification • Cognitive Radio • data fusion • Detection Theory • Distributed Detection • Engineering • Engineering: general • Forest Fire Detection • Imaging systems and technology • Minimax Hypothesis Testing • Parameter Estimation • pattern recognition • probability and statistics • Probability Metrics • Robust Detection • robust estimation • Robust Hypothesis Testing • sensor networks • Sequential Probability Ratio Test • Signal Detection • Signal, Image and Speech Processing • Signal Processing • Statistical Theory and Methods • Uncertainty Classes • Uncertainty Models
ISBN-10	3-319-49285-3 / 3319492853
ISBN-13	978-3-319-49285-8 / 9783319492858
Zustand	Neuware