Detection Of Signals In Noise

Author: Anthony D. Whalen
Publisher: Academic Press
ISBN: 1483220540
Size: 38.98 MB
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Detection of Signals in Noise serves as an introduction to the principles and applications of the statistical theory of signal detection. The book discusses probability and random processes; narrowband signals, their complex representation, and their properties described with the aid of the Hilbert transform; and Gaussian-derived processes. The text also describes the application of hypothesis testing for the detection of signals and the fundamentals required for statistical detection of signals in noise. Problem exercises, references, and a supplementary bibliography are included after each chapter. Students taking a graduate course in signal detection theory.

Signal Processing Noise

Author: Vyacheslav Tuzlukov
Publisher: CRC Press
ISBN: 1420041118
Size: 70.83 MB
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Additive and multiplicative noise in the information signal can significantly limit the potential of complex signal processing systems, especially when those systems use signals with complex phase structure. During the last few years this problem has been the focus of much research, and its solution could lead to profound improvements in applications of complex signals and coherent signal processing. Signal Processing Noise sets forth a generalized approach to signal processing in multiplicative and additive noise that represents a remarkable advance in signal processing and detection theory. This approach extends the boundaries of the noise immunity set by classical and modern signal processing theories, and systems constructed on this basis achieve better detection performance than that of systems currently in use. Featuring the results of the author's own research, the book is filled with examples and applications, and each chapter contains an analysis of recent observations obtained by computer modelling and experiments. Tables and illustrations clearly show the superiority of the generalized approach over both classical and modern approaches to signal processing noise. Addressing a fundamental problem in complex signal processing systems, this book offers not only theoretical development, but practical recommendations for raising noise immunity in a wide range of applications.

Maximum Entropy And Bayesian Methods

Author: Kenneth M. Hanson
Publisher: Springer Science & Business Media
ISBN: 9401154309
Size: 39.76 MB
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Proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods, Santa Fe, New Mexico, USA, 1995

Radar Detection

Author: Julius DiFranco
Publisher: IET
ISBN: 1891121367
Size: 15.91 MB
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"Corrected and reprinted version of a book originally published by Prentice-Hall, Englewood Cliff, NJ in 1968 and reprinted by Artech House Publishers, Norwood, MA in 1980"--Title page verso.

Radar Systems Peak Detection And Tracking

Author: Michael Kolawole
Publisher: Elsevier
ISBN: 0080515622
Size: 36.79 MB
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As well as being fully up-to-date, this book provides wider subject coverage than many other radar books. The inclusion of a chapter on Skywave Radar, and full consideration of HF / OTH issues makes this book especially relevant for communications engineers and the defence sector. * Explains key theory and mathematics from square one, using case studies where relevant * Designed so that mathematical sections can be skipped with no loss of continuity by those needing only a qualitative understanding * Theoretical content, presented alongside applications, and working examples, make the book suitable to students or others new to the subject as well as a professional reference

An Introduction To Signal Detection And Estimation

Author: H. Vincent Poor
Publisher: Springer Science & Business Media
ISBN: 1475738633
Size: 29.57 MB
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The purpose of this book is to introduce the reader to the basic theory of signal detection and estimation. It is assumed that the reader has a working knowledge of applied probabil ity and random processes such as that taught in a typical first-semester graduate engineering course on these subjects. This material is covered, for example, in the book by Wong (1983) in this series. More advanced concepts in these areas are introduced where needed, primarily in Chapters VI and VII, where continuous-time problems are treated. This book is adapted from a one-semester, second-tier graduate course taught at the University of Illinois. However, this material can also be used for a shorter or first-tier course by restricting coverage to Chapters I through V, which for the most part can be read with a background of only the basics of applied probability, including random vectors and conditional expectations. Sufficient background for the latter option is given for exam pIe in the book by Thomas (1986), also in this series.