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Essential Wavelets For Statistical Applications And Data Analysis
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Book Synopsis Essential Wavelets for Statistical Applications and Data Analysis by : R. Todd Ogden
Download or read book Essential Wavelets for Statistical Applications and Data Analysis written by R. Todd Ogden and published by . This book was released on 1997 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: A reference for advanced undergraduates with a knowledge of calculus, linear algebra, and basic statistical theory. Surveys new wavelet analysis tools and how they can be applied to fundamental data analysis problems. Emphasizing the methods rather than the mathematics, works through sample problems in such areas as non-parametric regression, density estimation, and time series spectral estimation. Annotation copyrighted by Book News, Inc., Portland, OR
Book Synopsis Essential Wavelets for Statistical Applications and Data Analysis by : Todd Ogden
Download or read book Essential Wavelets for Statistical Applications and Data Analysis written by Todd Ogden and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: I once heard the book by Meyer (1993) described as a "vulgarization" of wavelets. While this is true in one sense of the word, that of making a sub ject popular (Meyer's book is one of the early works written with the non specialist in mind), the implication seems to be that such an attempt some how cheapens or coarsens the subject. I have to disagree that popularity goes hand-in-hand with debasement. is certainly a beautiful theory underlying wavelet analysis, there is While there plenty of beauty left over for the applications of wavelet methods. This book is also written for the non-specialist, and therefore its main thrust is toward wavelet applications. Enough theory is given to help the reader gain a basic understanding of how wavelets work in practice, but much of the theory can be presented using only a basic level of mathematics. Only one theorem is for mally stated in this book, with only one proof. And these are only included to introduce some key concepts in a natural way.
Book Synopsis Essential Wavelets for Statistical Applications and Data Analysis by : Todd Ogden
Download or read book Essential Wavelets for Statistical Applications and Data Analysis written by Todd Ogden and published by Birkhäuser. This book was released on 2012-01-24 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: I once heard the book by Meyer (1993) described as a "vulgarization" of wavelets. While this is true in one sense of the word, that of making a sub ject popular (Meyer's book is one of the early works written with the non specialist in mind), the implication seems to be that such an attempt some how cheapens or coarsens the subject. I have to disagree that popularity goes hand-in-hand with debasement. is certainly a beautiful theory underlying wavelet analysis, there is While there plenty of beauty left over for the applications of wavelet methods. This book is also written for the non-specialist, and therefore its main thrust is toward wavelet applications. Enough theory is given to help the reader gain a basic understanding of how wavelets work in practice, but much of the theory can be presented using only a basic level of mathematics. Only one theorem is for mally stated in this book, with only one proof. And these are only included to introduce some key concepts in a natural way.
Book Synopsis Wavelets, Approximation, and Statistical Applications by : Wolfgang Härdle
Download or read book Wavelets, Approximation, and Statistical Applications written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The mathematical theory of ondelettes (wavelets) was developed by Yves Meyer and many collaborators about 10 years ago. It was designed for ap proximation of possibly irregular functions and surfaces and was successfully applied in data compression, turbulence analysis, image and signal process ing. Five years ago wavelet theory progressively appeared to be a power ful framework for nonparametric statistical problems. Efficient computa tional implementations are beginning to surface in this second lustrum of the nineties. This book brings together these three main streams of wavelet theory. It presents the theory, discusses approximations and gives a variety of statistical applications. It is the aim of this text to introduce the novice in this field into the various aspects of wavelets. Wavelets require a highly interactive computing interface. We present therefore all applications with software code from an interactive statistical computing environment. Readers interested in theory and construction of wavelets will find here in a condensed form results that are somewhat scattered around in the research literature. A practioner will be able to use wavelets via the available software code. We hope therefore to address both theory and practice with this book and thus help to construct bridges between the different groups of scientists. This te. xt grew out of a French-German cooperation (Seminaire Paris Berlin, Seminar Berlin-Paris). This seminar brings together theoretical and applied statisticians from Berlin and Paris. This work originates in the first of these seminars organized in Garchy, Burgundy in 1994.
Book Synopsis Wavelets and Statistics by : Anestis Antoniadis
Download or read book Wavelets and Statistics written by Anestis Antoniadis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite its short history, wavelet theory has found applications in a remarkable diversity of disciplines: mathematics, physics, numerical analysis, signal processing, probability theory and statistics. The abundance of intriguing and useful features enjoyed by wavelet and wavelet packed transforms has led to their application to a wide range of statistical and signal processing problems. On November 16-18, 1994, a conference on Wavelets and Statistics was held at Villard de Lans, France, organized by the Institute IMAG-LMC, Grenoble, France. The meeting was the 15th in the series of the Rencontres Pranco-Belges des 8tatisticiens and was attended by 74 mathematicians from 12 different countries. Following tradition, both theoretical statistical results and practical contributions of this active field of statistical research were presented. The editors and the local organizers hope that this volume reflects the broad spectrum of the conference. as it includes 21 articles contributed by specialists in various areas in this field. The material compiled is fairly wide in scope and ranges from the development of new tools for non parametric curve estimation to applied problems, such as detection of transients in signal processing and image segmentation. The articles are arranged in alphabetical order by author rather than subject matter. However, to help the reader, a subjective classification of the articles is provided at the end of the book. Several articles of this volume are directly or indirectly concerned with several as pects of wavelet-based function estimation and signal denoising.
Book Synopsis Wavelets in Functional Data Analysis by : Pedro A. Morettin
Download or read book Wavelets in Functional Data Analysis written by Pedro A. Morettin and published by Springer. This book was released on 2017-11-07 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wavelet-based procedures are key in many areas of statistics, applied mathematics, engineering, and science. This book presents wavelets in functional data analysis, offering a glimpse of problems in which they can be applied, including tumor analysis, functional magnetic resonance and meteorological data. Starting with the Haar wavelet, the authors explore myriad families of wavelets and how they can be used. High-dimensional data visualization (using Andrews' plots), wavelet shrinkage (a simple, yet powerful, procedure for nonparametric models) and a selection of estimation and testing techniques (including a discussion on Stein’s Paradox) make this a highly valuable resource for graduate students and experienced researchers alike.
Book Synopsis Wavelet Packets and Their Statistical Applications by : Khalil Ahmad
Download or read book Wavelet Packets and Their Statistical Applications written by Khalil Ahmad and published by Springer. This book was released on 2018-06-21 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basic concepts of functional analysis, wavelet analysis and thresholding. It begins with an elementary chapter on preliminaries such as basic concepts of functional analysis, a brief tour of the wavelet transform, Haar scaling functions and function space, wavelets, symlets wavelets and coiflets wavelets. In turn, Chapters 2 and 3 address the construction of wavelet packets, selected results on wavelet packets, band-limited wavelet packets, characterisations of wavelet packets, multiresolution analysis (MRA) wavelet packets, pointwise convergence, the convergence of wavelet packet series and convolution bounds. Chapter 4 discusses characterisations of function spaces like Lebesgue spaces, Hardy spaces and Sobolev spaces in terms of wavelet packets, while Chapter 5 is devoted to applications of wavelets and wavelet packets in speech denoising and biomedical signals. In closing, Chapter 6 highlights applications of wavelets and wavelet packets in image denoising.
Book Synopsis Computation and Applied Mathematics by :
Download or read book Computation and Applied Mathematics written by and published by . This book was released on 1996 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Wavelet Methods for Time Series Analysis by : Donald B. Percival
Download or read book Wavelet Methods for Time Series Analysis written by Donald B. Percival and published by Cambridge University Press. This book was released on 2006-02-27 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to wavelet analysis 'from the ground level and up', and to wavelet-based statistical analysis of time series focuses on practical discrete time techniques, with detailed descriptions of the theory and algorithms needed to understand and implement the discrete wavelet transforms. Numerous examples illustrate the techniques on actual time series. The many embedded exercises - with complete solutions provided in the Appendix - allow readers to use the book for self-guided study. Additional exercises can be used in a classroom setting. A Web site offers access to the time series and wavelets used in the book, as well as information on accessing software in S-Plus and other languages. Students and researchers wishing to use wavelet methods to analyze time series will find this book essential.
Book Synopsis Statistical Modeling by Wavelets by : Brani Vidakovic
Download or read book Statistical Modeling by Wavelets written by Brani Vidakovic and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, step-by-step introduction to wavelets in statistics. What are wavelets? What makes them increasingly indispensable in statistical nonparametrics? Why are they suitable for "time-scale" applications? How are they used to solve such problems as denoising, regression, or density estimation? Where can one find up-to-date information on these newly "discovered" mathematical objects? These are some of the questions Brani Vidakovic answers in Statistical Modeling by Wavelets. Providing a much-needed introduction to the latest tools afforded statisticians by wavelet theory, Vidakovic compiles, organizes, and explains in depth research data previously available only in disparate journal articles. He carefully balances both statistical and mathematical techniques, supplementing the material with a wealth of examples, more than 100 illustrations, and extensive references-with data sets and S-Plus wavelet overviews made available for downloading over the Internet. Both introductory and data-oriented modeling topics are featured, including: * Continuous and discrete wavelet transformations. * Statistical optimality properties of wavelet shrinkage. * Theoretical aspects of wavelet density estimation. * Bayesian modeling in the wavelet domain. * Properties of wavelet-based random functions and densities. * Several novel and important wavelet applications in statistics. * Wavelet methods in time series. Accessible to anyone with a background in advanced calculus and algebra, Statistical Modeling by Wavelets promises to become the standard reference for statisticians and engineers seeking a comprehensive introduction to an emerging field.
Book Synopsis Wavelet Analysis And Its Applications (In 2 Vols), Proceedings Of The Third International Conference On Waa by : Jian Ping Li
Download or read book Wavelet Analysis And Its Applications (In 2 Vols), Proceedings Of The Third International Conference On Waa written by Jian Ping Li and published by World Scientific. This book was released on 2003-04-11 with total page 1056 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book captures the essence of the current state of research in wavelet analysis and its applications, and identifies the changes and opportunities - both current and future - in the field. Distinguished researchers such as Prof John Daugman from Cambridge University and Prof Victor Wickerhauser from Washington University present their research papers.
Book Synopsis Wavelet Methods in Statistics with R by : Guy Nason
Download or read book Wavelet Methods in Statistics with R written by Guy Nason and published by Springer Science & Business Media. This book was released on 2010-07-25 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains information on how to tackle many important problems using a multiscale statistical approach. It focuses on how to use multiscale methods and discusses methodological and applied considerations.
Book Synopsis Nonparametric Statistics with Applications to Science and Engineering with R by : Paul Kvam
Download or read book Nonparametric Statistics with Applications to Science and Engineering with R written by Paul Kvam and published by John Wiley & Sons. This book was released on 2022-10-18 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: NONPARAMETRIC STATISTICS WITH APPLICATIONS TO SCIENCE AND ENGINEERING WITH R Introduction to the methods and techniques of traditional and modern nonparametric statistics, incorporating R code Nonparametric Statistics with Applications to Science and Engineering with R presents modern nonparametric statistics from a practical point of view, with the newly revised edition including custom R functions implementing nonparametric methods to explain how to compute them and make them more comprehensible. Relevant built-in functions and packages on CRAN are also provided with a sample code. R codes in the new edition not only enable readers to perform nonparametric analysis easily, but also to visualize and explore data using R’s powerful graphic systems, such as ggplot2 package and R base graphic system. The new edition includes useful tables at the end of each chapter that help the reader find data sets, files, functions, and packages that are used and relevant to the respective chapter. New examples and exercises that enable readers to gain a deeper insight into nonparametric statistics and increase their comprehension are also included. Some of the sample topics discussed in Nonparametric Statistics with Applications to Science and Engineering with R include: Basics of probability, statistics, Bayesian statistics, order statistics, Kolmogorov–Smirnov test statistics, rank tests, and designed experiments Categorical data, estimating distribution functions, density estimation, least squares regression, curve fitting techniques, wavelets, and bootstrap sampling EM algorithms, statistical learning, nonparametric Bayes, WinBUGS, properties of ranks, and Spearman coefficient of rank correlation Chi-square and goodness-of-fit, contingency tables, Fisher exact test, MC Nemar test, Cochran’s test, Mantel–Haenszel test, and Empirical Likelihood Nonparametric Statistics with Applications to Science and Engineering with R is a highly valuable resource for graduate students in engineering and the physical and mathematical sciences, as well as researchers who need a more comprehensive, but succinct understanding of modern nonparametric statistical methods.
Book Synopsis Wavelets from a Statistical Perspective by : Maarten Jansen
Download or read book Wavelets from a Statistical Perspective written by Maarten Jansen and published by CRC Press. This book was released on 2022-04-18 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wavelets from a Statistical Perspective offers a modern, 2nd generation look on wavelets, far beyond the rigid setting of the equispaced, dyadic wavelets in the early days. With the methods of this book, based on the lifting scheme, researchers can set up a wavelet or another multiresolution analysis adapted to their data, ranging from images to scattered data or other irregularly spaced observations. Whereas classical wavelets stand a bit apart from other nonparametric methods, this book adds a multiscale touch to your spline, kernel or local polynomial smoothing procedure, thereby extending its applicability to nonlinear, nonparametric processing for piecewise smooth data. One of the chapters of the book constructs B-spline wavelets on nonequispaced knots and multiscale local polynomial transforms. In another chapter, the link between wavelets and Fourier analysis, ubiquitous in the classical approach, is explained, but without being inevitable. In further chapters the discrete wavelet transform is contrasted with the continuous version, the nondecimated (or maximal overlap) transform taking an intermediate position. An important principle in designing a wavelet analysis through the lifting scheme is finding the right balance between bias and variance. Bias and variance also play a crucial role in the nonparametric smoothing in a wavelet framework, in finding well working thresholds or other smoothing parameters. The numerous illustrations can be reproduced with the online available, accompanying software. The software and the exercises can also be used as a starting point in the further exploration of the material.
Book Synopsis Wavelets and their Applications by : Michel Misiti
Download or read book Wavelets and their Applications written by Michel Misiti and published by John Wiley & Sons. This book was released on 2013-03-01 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last 15 years have seen an explosion of interest in wavelets with applications in fields such as image compression, turbulence, human vision, radar and earthquake prediction. Wavelets represent an area that combines signal in image processing, mathematics, physics and electrical engineering. As such, this title is intended for the wide audience that is interested in mastering the basic techniques in this subject area, such as decomposition and compression.
Book Synopsis An Introduction to Wavelets and Other Filtering Methods in Finance and Economics by : Ramazan Gençay
Download or read book An Introduction to Wavelets and Other Filtering Methods in Finance and Economics written by Ramazan Gençay and published by Elsevier. This book was released on 2001-10-12 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics. It emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series. It offers testing issues which can be performed with wavelets in conjunction with the multi-resolution analysis. The descriptive focus of the book avoids proofs and provides easy access to a wide spectrum of parametric and nonparametric filtering methods. Examples and empirical applications will show readers the capabilities, advantages, and disadvantages of each method. - The first book to present a unified view of filtering techniques - Concentrates on exactly what wavelets analysis and filtering methods in general can reveal about a time series - Provides easy access to a wide spectrum of parametric and non-parametric filtering methods
Book Synopsis Discrete Wavelet Transforms by : Dr. Awad Al-Asmari
Download or read book Discrete Wavelet Transforms written by Dr. Awad Al-Asmari and published by BoD – Books on Demand. This book was released on 2013-02-06 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete Wavelet Transform is a wavelet (DWT) transform that is widely used in numerical and functional analysis. Its key advantage over more traditional transforms, such as the Fourier transform, lies in its ability to offer temporal resolution, i.e. it captures both frequency and location (or time) information. This book presents a succinct compendium of some of the more recent variants of DWTs and their use to come up with solutions to an array of problems transcending the traditional application areas of image/video processing and security to the relatively newer areas of medicine, artificial intelligence, power systems and telecommunications. The first of the two sections of this book contains three chapters devoted to traditional applications of DWTs in digital image compression, copyright protection and video resolution enhancement. The second section, comprising of five chapters, is devoted to variants of the DWT and their applications in humanoid-robot vision systems; modeling and simulation recognition of physiological and behavioral traits through human gait and facial images; assessment of agitation and sedation in intensive care patients; maximization of power control systems; and, finally, in demodulation of FM data in free-space optical control systems.
