Statistical And Adaptive Signal Processing
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Statistical And Adaptive Signal Processing
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Author : Dimitris G. Manolakis
language : en
Publisher: Artech House Publishers
Release Date : 2005
Statistical And Adaptive Signal Processing written by Dimitris G. Manolakis and has been published by Artech House Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Technology & Engineering categories.
This authoritative volume on statistical and adaptive signal processing offers you a unified, comprehensive and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. Packed with over 3,000 equations and more than 300 illustrations, this unique resource provides you with balanced coverage of implementation issues, applications, and theory, making it a smart choice for professional engineers and students alike.
Partial Update Adaptive Signal Processing
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Author : Kutluyil Dogancay
language : en
Publisher: Academic Press
Release Date : 2008-09-17
Partial Update Adaptive Signal Processing written by Kutluyil Dogancay and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-17 with Technology & Engineering categories.
Partial-update adaptive signal processing algorithms not only permit significant complexity reduction in adaptive filter implementations, but can also improve adaptive filter performance in telecommunications applications. This book gives state-of-the-art methods for the design and development of partial-update adaptive signal processing algorithms for use in systems development. Partial-Update Adaptive Signal Processing provides a comprehensive coverage of key partial updating schemes, giving detailed information on the theory and applications of acoustic and network echo cancellation, channel equalization and multiuser detection. It also examines convergence and stability issues for partial update algorithms, providing detailed complexity analysis and a unifying treatment of partial-update techniques. Features: • Advanced analysis and design tools • Application examples illustrating the use of partial-update adaptive signal processing • MATLAB codes for developed algorithms This unique reference will be of interest to signal processing and communications engineers, researchers, R&D engineers and graduate students. "This is a very systematic and methodical treatment of an adaptive signal processing topic, of particular significance in power limited applications such as in wireless communication systems and smart ad hoc sensor networks. I am very happy to have this book on my shelf, not to gather dust, but to be consulted and used in my own research and teaching activities" – Professor A. G. Constantinides, Imperial College, London About the author: Kutluyil Dogançay is an associate professor of Electrical Engineering at the University of South Australia. His research interests span statistical and adaptive signal processing and he serves as a consultant to defence and private industry. He was the Signal Processing and Communications Program Chair of IDC Conference 2007, and is currently chair of the IEEE South Australia Communications and Signal Processing Chapter. Advanced analysis and design tools Algorithm summaries in tabular format Case studies illustrate the application of partial update adaptive signal processing
Adaptive Signal Processing
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Author : Tülay Adali
language : en
Publisher: John Wiley & Sons
Release Date : 2010-06-25
Adaptive Signal Processing written by Tülay Adali and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-25 with Science categories.
Leading experts present the latest research results in adaptive signal processing Recent developments in signal processing have made it clear that significant performance gains can be achieved beyond those achievable using standard adaptive filtering approaches. Adaptive Signal Processing presents the next generation of algorithms that will produce these desired results, with an emphasis on important applications and theoretical advancements. This highly unique resource brings together leading authorities in the field writing on the key topics of significance, each at the cutting edge of its own area of specialty. It begins by addressing the problem of optimization in the complex domain, fully developing a framework that enables taking full advantage of the power of complex-valued processing. Then, the challenges of multichannel processing of complex-valued signals are explored. This comprehensive volume goes on to cover Turbo processing, tracking in the subspace domain, nonlinear sequential state estimation, and speech-bandwidth extension. Examines the seven most important topics in adaptive filtering that will define the next-generation adaptive filtering solutions Introduces the powerful adaptive signal processing methods developed within the last ten years to account for the characteristics of real-life data: non-Gaussianity, non-circularity, non-stationarity, and non-linearity Features self-contained chapters, numerous examples to clarify concepts, and end-of-chapter problems to reinforce understanding of the material Contains contributions from acknowledged leaders in the field Adaptive Signal Processing is an invaluable tool for graduate students, researchers, and practitioners working in the areas of signal processing, communications, controls, radar, sonar, and biomedical engineering.
Statistical Digital Signal Processing And Modeling
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Author : Monson H. Hayes
language : en
Publisher: John Wiley & Sons
Release Date : 1996-04-11
Statistical Digital Signal Processing And Modeling written by Monson H. Hayes and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-04-11 with Technology & Engineering categories.
This text explores the application of signal modelling to problems encountered in optimal filtering, spectrum estimation and adaptive filtering. Coverage is divided equally between the theory of statistical signal processing and the algorithms used to solve problems.
Adaptive Filtering
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Author : Paulo S R Diniz
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Adaptive Filtering written by Paulo S R Diniz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
The field of Digital Signal Processing has developed so fast in the last two decades that it can be found in the graduate and undergraduate programs of most universities. This development is related to the growing available techno logies for implementing digital signal processing algorithms. The tremendous growth of development in the digital signal processing area has turned some of its specialized areas into fields themselves. If accurate information of the signals to be processed is available, the designer can easily choose the most appropriate algorithm to process the signal. When dealing with signals whose statistical properties are unknown, fixed algorithms do not process these signals efficiently. The solution is to use an adaptive filter that automatically changes its characteristics by optimizing the internal parameters. The adaptive filtering algorithms are essential in many statistical signal processing applications. Although the field of adaptive signal processing has been subject of research for over three decades, it was in the eighties that a major growth occurred in research and applications. Two main reasons can be credited to this growth, the availability of implementation tools and the appearance of early textbooks exposing the subject in an organized form. Presently, there is still a lot of activities going on in the area of adaptive filtering. In spite of that, the theor etical development in the linear-adaptive-filtering area reached a maturity that justifies a text treating the various methods in a unified way, emphasizing the algorithms that work well in practical implementation.
Algorithms For Statistical Signal Processing
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Author : John G. Proakis
language : en
Publisher:
Release Date : 2002
Algorithms For Statistical Signal Processing written by John G. Proakis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
Keeping pace with the expanding, ever more complex applications of DSP, this authoritative presentation of computational algorithms for statistical signal processing focuses on "advanced topics" ignored by other books on the subject. Algorithms for Convolution and DFT. Linear Prediction and Optimum Linear Filters. Least-Squares Methods for System Modeling and Filter Design. Adaptive Filters. Recursive Least-Squares Algorithms for Array Signal Processing. QRD-Based Fast Adaptive Filter Algorithms. Power Spectrum Estimation. Signal Analysis with Higher-Order Spectra. For Electrical Engineers, Computer Engineers, Computer Scientists, and Applied Mathematicians.
Adaptive Signal Processing
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Author : Thomas S. Alexander
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Adaptive Signal Processing written by Thomas S. Alexander and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
The creation of the text really began in 1976 with the author being involved with a group of researchers at Stanford University and the Naval Ocean Systems Center, San Diego. At that time, adaptive techniques were more laboratory (and mental) curiosities than the accepted and pervasive categories of signal processing that they have become. Over the lasl 10 years, adaptive filters have become standard components in telephony, data communications, and signal detection and tracking systems. Their use and consumer acceptance will undoubtedly only increase in the future. The mathematical principles underlying adaptive signal processing were initially fascinating and were my first experience in seeing applied mathematics work for a paycheck. Since that time, the application of even more advanced mathematical techniques have kept the area of adaptive signal processing as exciting as those initial days. The text seeks to be a bridge between the open literature in the professional journals, which is usually quite concentrated, concise, and advanced, and the graduate classroom and research environment where underlying principles are often more important.
Adaptive Signal Processing
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Author : Widrow
language : en
Publisher: Pearson Education India
Release Date : 2016
Adaptive Signal Processing written by Widrow and has been published by Pearson Education India this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Adaptive Signal Processing
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Author : L.D. Davisson
language : en
Publisher: Springer
Release Date : 2014-05-04
Adaptive Signal Processing written by L.D. Davisson and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-04 with Computers categories.
The four chapters of this volume, written by prominent workers in the field of adaptive processing and linear prediction, address a variety of problems, ranging from adaptive source coding to autoregressive spectral estimation. The first chapter, by T.C. Butash and L.D. Davisson, formulates the performance of an adaptive linear predictor in a series of theorems, with and without the Gaussian assumption, under the hypothesis that its coefficients are derived from either the (single) observation sequence to be predicted (dependent case) or a second, statistically independent realisation (independent case). The contribution by H.V. Poor reviews three recently developed general methodologies for designing signal predictors under nonclassical operating conditions, namely the robust predictor, the high-speed Levinson modeling, and the approximate conditional mean nonlinear predictor. W. Wax presents the key concepts and techniques for detecting, localizing and beamforming multiple narrowband sources by passive sensor arrays. Special coding algorithms and techniques based on the use of linear prediction now permit high-quality voice reproduction at remorably low bit rates. The paper by A. Gersho reviews some of the main ideas underlying the algorithms of major interest today.
Unsupervised Signal Processing
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Author : João Marcos Travassos Romano
language : en
Publisher: CRC Press
Release Date : 2018-09-03
Unsupervised Signal Processing written by João Marcos Travassos Romano and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Computers categories.
Unsupervised Signal Processing: Channel Equalization and Source Separation provides a unified, systematic, and synthetic presentation of the theory of unsupervised signal processing. Always maintaining the focus on a signal processing-oriented approach, this book describes how the subject has evolved and assumed a wider scope that covers several topics, from well-established blind equalization and source separation methods to novel approaches based on machine learning and bio-inspired algorithms. From the foundations of statistical and adaptive signal processing, the authors explore and elaborate on emerging tools, such as machine learning-based solutions and bio-inspired methods. With a fresh take on this exciting area of study, this book: Provides a solid background on the statistical characterization of signals and systems and on linear filtering theory Emphasizes the link between supervised and unsupervised processing from the perspective of linear prediction and constrained filtering theory Addresses key issues concerning equilibrium solutions and equivalence relationships in the context of unsupervised equalization criteria Provides a systematic presentation of source separation and independent component analysis Discusses some instigating connections between the filtering problem and computational intelligence approaches. Building on more than a decade of the authors’ work at DSPCom laboratory, this book applies a fresh conceptual treatment and mathematical formalism to important existing topics. The result is perhaps the first unified presentation of unsupervised signal processing techniques—one that addresses areas including digital filters, adaptive methods, and statistical signal processing. With its remarkable synthesis of the field, this book provides a new vision to stimulate progress and contribute to the advent of more useful, efficient, and friendly intelligent systems.