SVD and Signal Processing, III

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Publisher : Elsevier
ISBN 13 : 9780080542157
Total Pages : 485 pages
Book Rating : 4.58/5 ( download)

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Book Synopsis SVD and Signal Processing, III by : M. Moonen

Download or read book SVD and Signal Processing, III written by M. Moonen and published by Elsevier. This book was released on 1995-03-16 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matrix Singular Value Decomposition (SVD) and its application to problems in signal processing is explored in this book. The papers discuss algorithms and implementation architectures for computing the SVD, as well as a variety of applications such as systems and signal modeling and detection. The publication presents a number of keynote papers, highlighting recent developments in the field, namely large scale SVD applications, isospectral matrix flows, Riemannian SVD and consistent signal reconstruction. It also features a translation of a historical paper by Eugenio Beltrami, containing one of the earliest published discussions of the SVD. With contributions sourced from internationally recognised scientists, the book will be of specific interest to all researchers and students involved in the SVD and signal processing field.

SVD and Signal Processing

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Publisher :
ISBN 13 :
Total Pages : 500 pages
Book Rating : 4.61/5 ( download)

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Book Synopsis SVD and Signal Processing by : Ed. F. Deprettere

Download or read book SVD and Signal Processing written by Ed. F. Deprettere and published by . This book was released on 1988 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compiled in this book is a selection of articles written by internationally recognized experts in the fields of matrix computation and signal processing. In almost all digital signal processing (DSR) problems, the available data is corrupted by (measurement) noise or is incomplete. Classical techniques are unable to separate ''signal'' spaces and ''noise'' spaces. However, the information hidden in the data can be made explicit through singular value decomposition (SVD). SVD based signal processing is making headway and will become feasible soon, thanks to the progress in parallel computations and VLSI implementation. The book is divided into six parts. Part one is a tutorial, beginning with an introduction, including (VLSI) parallel algorithms and some intriguing problems. It describes several applications of SVD in system identification and signal detection. It also deals with the fundamental harmonic retrieval problem and principal component analysis. Part two discusses details of model reduction, system identification and detection of multiple sinusoids in white noise, while part three is devoted to the total-least-squares and generalized singular value decomposition problems. The fourth section deals with real-time and adaptive algorithms, the fifth examines fast algorithms and architectures, such as block-algorithms, computational arrays, systolic arrays, hypercubes and connection machines, and the final part addresses some open problems.

Singular Spectrum Analysis for Time Series

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Publisher : Springer Science & Business Media
ISBN 13 : 3642349137
Total Pages : 126 pages
Book Rating : 4.33/5 ( download)

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Book Synopsis Singular Spectrum Analysis for Time Series by : Nina Golyandina

Download or read book Singular Spectrum Analysis for Time Series written by Nina Golyandina and published by Springer Science & Business Media. This book was released on 2013-01-19 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA seeks to decompose the original series into a sum of a small number of interpretable components such as trend, oscillatory components and noise. It is based on the singular value decomposition of a specific matrix constructed upon the time series. Neither a parametric model nor stationarity are assumed for the time series. This makes SSA a model-free method and hence enables SSA to have a very wide range of applicability. The present book is devoted to the methodology of SSA and shows how to use SSA both safely and with maximum effect. Potential readers of the book include: professional statisticians and econometricians, specialists in any discipline in which problems of time series analysis and forecasting occur, specialists in signal processing and those needed to extract signals from noisy data, and students taking courses on applied time series analysis.

Wireless Algorithms, Systems, and Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 3642146538
Total Pages : 381 pages
Book Rating : 4.34/5 ( download)

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Book Synopsis Wireless Algorithms, Systems, and Applications by : Gopal Pandurangan

Download or read book Wireless Algorithms, Systems, and Applications written by Gopal Pandurangan and published by Springer Science & Business Media. This book was released on 2010-07-30 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th Annual International Conference on Wireless Algorithms, Systems, and Applications, WASA 2010, held in Beijing, China, in August 2010. The 19 revised full papers and 10 revised short papers presented together with 18 papers from 4 workshops were carefully reviewed and selected from numerous submissions. The papers are organized in topica sections on topology control and coverage, theoretical foundations, energy-aware algorithms and protocol design, wireless sensor networks and applications, applications and experimentation, scheduling and channel assignment, coding, information theory and security, security of wireless and ad-hoc networks, data management and network control in wireless networks, radar and sonar sensor networks, as well as compressive sensing for communications and networking.

Independent Component Analysis and Signal Separation

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Publisher : Springer
ISBN 13 : 3642005993
Total Pages : 803 pages
Book Rating : 4.92/5 ( download)

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Book Synopsis Independent Component Analysis and Signal Separation by : Tulay Adali

Download or read book Independent Component Analysis and Signal Separation written by Tulay Adali and published by Springer. This book was released on 2009-03-16 with total page 803 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation, ICA 2009, held in Paraty, Brazil, in March 2009. The 97 revised papers presented were carefully reviewed and selected from 137 submissions. The papers are organized in topical sections on theory, algorithms and architectures, biomedical applications, image processing, speech and audio processing, other applications, as well as a special session on evaluation.

Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms

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Publisher : Springer Science & Business Media
ISBN 13 : 3642755364
Total Pages : 717 pages
Book Rating : 4.61/5 ( download)

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Book Synopsis Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms by : Gene H. Golub

Download or read book Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms written by Gene H. Golub and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical linear algebra, digital signal processing, and parallel algorithms are three disciplines with a great deal of activity in the last few years. The interaction between them has been growing to a level that merits an Advanced Study Institute dedicated to the three areas together. This volume gives an account of the main results in this interdisciplinary field. The following topics emerged as major themes of the meeting: - Singular value and eigenvalue decompositions, including applications, - Toeplitz matrices, including special algorithms and architectures, - Recursive least squares in linear algebra, digital signal processing and control, - Updating and downdating techniques in linear algebra and signal processing, - Stability and sensitivity analysis of special recursive least squares problems, - Special architectures for linear algebra and signal processing. This book contains tutorials on these topics given by leading scientists in each of the three areas. A consider- able number of new research results are presented in contributed papers. The tutorials and papers will be of value to anyone interested in the three disciplines.

A Practical Approach to Microarray Data Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 0306478153
Total Pages : 382 pages
Book Rating : 4.54/5 ( download)

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Book Synopsis A Practical Approach to Microarray Data Analysis by : Daniel P. Berrar

Download or read book A Practical Approach to Microarray Data Analysis written by Daniel P. Berrar and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.

Optimum Signal Processing

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Publisher :
ISBN 13 : 9780979371301
Total Pages : 377 pages
Book Rating : 4.09/5 ( download)

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Book Synopsis Optimum Signal Processing by : Sophocles J. Orfanidis

Download or read book Optimum Signal Processing written by Sophocles J. Orfanidis and published by . This book was released on 2007 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt:

SVD and Signal Processing, II

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Publisher : Elsevier Publishing Company
ISBN 13 :
Total Pages : 534 pages
Book Rating : 4.33/5 ( download)

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Book Synopsis SVD and Signal Processing, II by : Richard J. Vaccaro

Download or read book SVD and Signal Processing, II written by Richard J. Vaccaro and published by Elsevier Publishing Company. This book was released on 1991 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is an outgrowth of the 2nd International Workshop on SVD and Signal Processing which was held in Kingston, Rhode Island, 25-27 June, 1990. The singular value decomposition (SVD) has been applied to signal processing problems since the late 1970's, although it has been known in various forms for over 100 years. SVD filtering has been shown to give better results at lower signal-to-noise ratios than classical techniques based on linear filtering. This explains in part the recent interest in SVD techniques for signal processing. This book is a compilation of papers that examine in detail the singular decomposition of a matrix and its application to problems in signal processing. Algorithms and implementation architectures for computing the SVD are discussed, and analysis techniques for predicting and understanding the performance of SVD-based algorithms are given. The volume will provide both a stimulus for future research in this field as well as useful reference material for many years to come.

Data-Driven Science and Engineering

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Publisher : Cambridge University Press
ISBN 13 : 1009098489
Total Pages : 615 pages
Book Rating : 4.89/5 ( download)

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Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton

Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLABĀ®.