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Author: Jerry D. Gibson
Publisher: Academic Press
ISBN: 0080956289
Category : Computers
Languages : en
Pages : 255
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Book Description
Even with the advances in signal processing and digital communications, robustness to uncertain channel statistics continues to be a fundamental issue in the design and performance analysis of today's communications, radar, and sonar systems. The variability of digital communications systems consistently challenges the communications system designer, while new applications have channels that almost defy accurate modeling. As a result, parametric detectors, which are excellent when model assumptions are satisfied, do not maintain the satisfactory performance necessary for detection. This core IEEE Press reissue is the only book devoted solely to nonparametric detection - the key to maintaining good performance over a wide range of conditions. Throughout, the authors employ the classical Neyman-Pearson approach, which is widely applicable to detection problems in communications, radar, sonar, acoustics, and geophysics. Topics covered include: nonparametric detection theory, basic detection theory, one-input and two-input detectors and performance, tied observations, dependent sample performance, and engineering applications.
Author: Jerry D. Gibson
Publisher: Academic Press
ISBN: 0080956289
Category : Computers
Languages : en
Pages : 255
Get Book Here
Book Description
Even with the advances in signal processing and digital communications, robustness to uncertain channel statistics continues to be a fundamental issue in the design and performance analysis of today's communications, radar, and sonar systems. The variability of digital communications systems consistently challenges the communications system designer, while new applications have channels that almost defy accurate modeling. As a result, parametric detectors, which are excellent when model assumptions are satisfied, do not maintain the satisfactory performance necessary for detection. This core IEEE Press reissue is the only book devoted solely to nonparametric detection - the key to maintaining good performance over a wide range of conditions. Throughout, the authors employ the classical Neyman-Pearson approach, which is widely applicable to detection problems in communications, radar, sonar, acoustics, and geophysics. Topics covered include: nonparametric detection theory, basic detection theory, one-input and two-input detectors and performance, tied observations, dependent sample performance, and engineering applications.
Author: E. Brodsky
Publisher: Springer Science & Business Media
ISBN: 9780792321224
Category : Mathematics
Languages : en
Pages : 228
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Book Description
The explosive development of information science and technology puts in new problems involving statistical data analysis. These problems result from higher re quirements concerning the reliability of statistical decisions, the accuracy of math ematical models and the quality of control in complex systems. A new aspect of statistical analysis has emerged, closely connected with one of the basic questions of cynergetics: how to "compress" large volumes of experimental data in order to extract the most valuable information from data observed. De tection of large "homogeneous" segments of data enables one to identify "hidden" regularities in an object's behavior, to create mathematical models for each seg ment of homogeneity, to choose an appropriate control, etc. Statistical methods dealing with the detection of changes in the characteristics of random processes can be of great use in all these problems. These methods have accompanied the rapid growth in data beginning from the middle of our century. According to a tradition of more than thirty years, we call this sphere of statistical analysis the "theory of change-point detection. " During the last fifteen years, we have witnessed many exciting developments in the theory of change-point detection. New promising directions of research have emerged, and traditional trends have flourished anew. Despite this, most of the results are widely scattered in the literature and few monographs exist. A real need has arisen for up-to-date books which present an account of important current research trends, one of which is the theory of non parametric change--point detection.
Author: H. Vincent Poor
Publisher: Springer Science & Business Media
ISBN: 1475723415
Category : Technology & Engineering
Languages : en
Pages : 405
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Book Description
Essential background reading for engineers and scientists working in such fields as communications, control, signal, and image processing, radar and sonar, radio astronomy, seismology, remote sensing, and instrumentation. The book can be used as a textbook for a single course, as well as a combination of an introductory and an advanced course, or even for two separate courses, one in signal detection, the other in estimation.
Author: Yuri Ingster
Publisher: Springer Science & Business Media
ISBN: 0387215808
Category : Mathematics
Languages : en
Pages : 471
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Book Description
This book presents the modern theory of nonparametric goodness-of-fit testing. It fills the gap in modern nonparametric statistical theory by discussing hypothesis testing and addresses mathematical statisticians who are interesting in the theory of non-parametric statistical inference. It will be of interest to specialists who are dealing with applied non-parametric statistical problems relevant in signal detection and transmission and in technical and medical diagnostics among others.
Author: Iickho Song
Publisher: Springer Science & Business Media
ISBN: 3662048590
Category : Technology & Engineering
Languages : en
Pages : 403
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Book Description
This monograph contains a number of problems with signal detection theory, presenting a generalized observation model for signal detection problems. The model includes several interesting and common special cases, such as those describing additive noise, multiplicative noise and signal-dependent noise.
Author: Grzegorz Mzyk
Publisher: Springer
ISBN: 3319035967
Category : Technology & Engineering
Languages : en
Pages : 245
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Book Description
This book considers a problem of block-oriented nonlinear dynamic system identification in the presence of random disturbances. This class of systems includes various interconnections of linear dynamic blocks and static nonlinear elements, e.g., Hammerstein system, Wiener system, Wiener-Hammerstein ("sandwich") system and additive NARMAX systems with feedback. Interconnecting signals are not accessible for measurement. The combined parametric-nonparametric algorithms, proposed in the book, can be selected dependently on the prior knowledge of the system and signals. Most of them are based on the decomposition of the complex system identification task into simpler local sub-problems by using non-parametric (kernel or orthogonal) regression estimation. In the parametric stage, the generalized least squares or the instrumental variables technique is commonly applied to cope with correlated excitations. Limit properties of the algorithms have been shown analytically and illustrated in simple experiments.
Author: Library of Congress
Publisher:
ISBN:
Category : Subject headings, Library of Congress
Languages : en
Pages : 1160
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Book Description
Author: Library of Congress. Cataloging Policy and Support Office
Publisher:
ISBN:
Category : Subject headings, Library of Congress
Languages : en
Pages : 1596
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Book Description
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: Fouzi Harrou
Publisher: Elsevier
ISBN: 0128234334
Category : Transportation
Languages : en
Pages : 270
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Book Description
Road Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. The book examines commonly used traffic analysis methodologies as well the emerging methods that use deep learning methods. Other sections discuss how to understand statistical models and machine learning algorithms and how to apply them to traffic modeling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, this book is ideal for researchers and practitioners who want to improve the performance of intelligent transportation systems. - Provides integrated, up-to-date and complete coverage of the key components for intelligent transportation systems: traffic modeling, forecasting, estimation and monitoring - Uses methods based on video and time series data for traffic modeling and forecasting - Includes case studies, key processes guidance and comparisons of different methodologies
