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Author: Saleem A. Kassam
Publisher: Springer Science & Business Media
ISBN: 146123834X
Category : Technology & Engineering
Languages : en
Pages : 244
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Book Description
This book contains a unified treatment of a class of problems of signal detection theory. This is the detection of signals in addi tive noise which is not required to have Gaussian probability den sity functions in its statistical description. For the most part the material developed here can be classified as belonging to the gen eral body of results of parametric theory. Thus the probability density functions of the observations are assumed to be known, at least to 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 con sidered in this book. Three canonical problems of signal detection in additive noise are covered here. These allow between them formulation of a range of specific detection problems arising in applications such as radar and sonar, binary signaling, and pattern recognition and classification. The simplest to state and perhaps the most widely studied of all is the problem of detecting a completely known deterministic signal in noise. Also considered here is the detection random non-deterministic signal in noise. Both of these situa of a tions may arise for observation processes of the low-pass type and also for processes of the band-pass type.
Author: Saleem A. Kassam
Publisher: Springer Science & Business Media
ISBN: 146123834X
Category : Technology & Engineering
Languages : en
Pages : 244
Get Book
Book Description
This book contains a unified treatment of a class of problems of signal detection theory. This is the detection of signals in addi tive noise which is not required to have Gaussian probability den sity functions in its statistical description. For the most part the material developed here can be classified as belonging to the gen eral body of results of parametric theory. Thus the probability density functions of the observations are assumed to be known, at least to 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 con sidered in this book. Three canonical problems of signal detection in additive noise are covered here. These allow between them formulation of a range of specific detection problems arising in applications such as radar and sonar, binary signaling, and pattern recognition and classification. The simplest to state and perhaps the most widely studied of all is the problem of detecting a completely known deterministic signal in noise. Also considered here is the detection random non-deterministic signal in noise. Both of these situa of a tions may arise for observation processes of the low-pass type and also for processes of the band-pass type.
Author: Saleem A. Kassam
Publisher:
ISBN: 9787506213127
Category : Signal theory (Telecommunication)
Languages : en
Pages : 234
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Book Description
Author: Edward J. Wegman
Publisher: Springer Science & Business Media
ISBN: 1461388597
Category : Technology & Engineering
Languages : en
Pages : 246
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Book Description
Non-Gaussian Signal Processing is a child of a technological push. It is evident that we are moving from an era of simple signal processing with relatively primitive electronic cir cuits to one in which digital processing systems, in a combined hardware-software configura. tion, are quite capable of implementing advanced mathematical and statistical procedures. Moreover, as these processing techniques become more sophisticated and powerful, the sharper resolution of the resulting system brings into question the classic distributional assumptions of Gaussianity for both noise and signal processes. This in turn opens the door to a fundamental reexamination of structure and inference methods for non-Gaussian sto chastic processes together with the application of such processes as models in the context of filtering, estimation, detection and signal extraction. Based on the premise that such a fun damental reexamination was timely, in 1981 the Office of Naval Research initiated a research effort in Non-Gaussian Signal Processing under the Selected Research Opportunities Program.
Author: Anthony D. Whalen
Publisher: Academic Press
ISBN: 1483220540
Category : Technology & Engineering
Languages : en
Pages : 429
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Book Description
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.
Author: Vyacheslav P. Tuzlukov
Publisher: Springer Science & Business Media
ISBN: 146120187X
Category : Technology & Engineering
Languages : en
Pages : 741
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Book Description
Increasing the noise immunity of complex signal processing systems is the main problem in various areas of signal processing. At the present time there are many books and periodical articles devoted to signal detection, but many important problems remain to be solved. New approaches to complex problems allow us not only to summarize investigations, but also to improve the quality of signal detection in noise. This book is devoted to fundamental problems in the generalized approach to signal processing in noise based on a seemingly abstract idea: the introduction of an additional noise source that does not carry any information about the signal in order to improve the qualitative performance of complex signal processing systems. Theoretical and experimental studies carried out by the author lead to the conclusion that the proposed generalized approach to signal processing in noise allows us to formulate a decision-making rule based on the determi nation of the jointly sufficient statistics of the mean and variance of the likelihood function (or functional). Classical and modern signal detection theories allow us to define only the sufficient statistic of the mean of the likelihood function (or functional). The presence of additional information about the statistical characteristics of the like lihood function (or functional) leads to better-quality signal detection in comparison with the optimal signal detection algorithms of classical and modern theories.
Author: Iickho Song
Publisher: Springer Science & Business Media
ISBN: 9783540430643
Category : Computers
Languages : en
Pages : 416
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Book Description
This book contains a number of problems of signal detection theory. A generalized observation model for signal detection problems is included. The model includes several interesting and common special cases such as those describing additive noise, multiplicative noise, and signal-dependent noise. The model can also describe composite signals in addition to the usual known (deterministic) signals and random (stochastic) signals. Locally optimum (LO) and locally optimum rank (LOR) detectors for known and random signals in the model are discussed, and original results are obtained. Other approaches to detection of signals are also discussed.
Author: Robert N. McDonough
Publisher:
ISBN: 9780127448527
Category : Science
Languages : en
Pages : 495
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Book Description
The updated revision to the authors' successful and widely used introduction to the principles and applciation of the statistical theory of signal detection. The book emphasizes those theories that have been found to be particularly useful in practice, including principles applied to detection problems encountered in digital communications, radar, and sonar.
Author: John C. Hancock
Publisher:
ISBN:
Category : Information theory
Languages : en
Pages : 264
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Book Description
Written as a second course for graduate students.
Author: Vyacheslav Tuzlukov
Publisher: CRC Press
ISBN: 1420041118
Category : Technology & Engineering
Languages : en
Pages : 688
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Book Description
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.
Author: Max A. Little
Publisher: Oxford University Press, USA
ISBN: 0198714939
Category : Computers
Languages : en
Pages : 378
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Book Description
Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.
