Signal Detection in Non-Gaussian Noise
By: by Saleem A. Kassam
Series: Springer Texts in Electrical Engineering; Springer texts in electrical engineering
Publisher: Springer New York
Published: 1988
Place of publication: New York, NY
Language: eng
Format: [electronic resource] /
Number of pages: 234
ISBN-13: 9781461283706; 9781461238348
Subjects: Engineering; Telecommunication
Description: This book contains a unified treatment of a class of problems of signal detection theory. This is the detection of signals in additive noise which is not required to have Gaussian probability density functions in its statistical description. For the most part the material developed here can be classified as belonging to the general body of results of parametric theory. Thus the probability density functions of the observations are assumed to be known, at least within a finite number of unknown parameters in a known functional form. Of course the focus is on noise which is not Gaussian; results for Gaussian noise in the problems treated here become special cases. The contents also form a bridge between the classical results of signal detection in Gaussian noise and those of nonparametric and robust signal detection, which are not considered in this book.
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Table of contents: title: Contents: Elements of Statistical Hypothesis Testing; title: Detection of Known Signals in Additive Noise; title: Some Univariate Noise Probability Density Function Models; title: Optimum Data Quantization in Known-Signal Detection; title: Detection of Known Narrowband Signals in Narrowband Noise; title: Detection of Narrowband Signals with Random Phase Angles; title: Detection of Random Signals in Additive Noise; title: References; title: Index.