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Wavelet Analysis
The International Conference of Computational Harmonic Analysis, held in Hong Kong during the period of June 4 OCo 8, 2001, brought together mathematicians and engineers interested in the computational aspects of harmonic analysis. Plenary speakers include W Dahmen, R Q Jia, P W Jones, K S Lau, S L Lee, S Smale, J Smoller, G Strang, M Vetterlli, and M V Wickerhauser. The central theme was wavelet analysis in the broadest sense, covering time-frequency and time-scale analysis, filter banks, fast numerical computations, spline methods, multiscale algorithms, approximation theory, signal processing, and a great variety of applications.This proceedings volume contains sixteen papers from the lectures given by plenary and invited speakers. These include expository articles surveying various aspects of the twenty-year development of wavelet analysis, and original research papers reflecting the wide range of research topics of current interest."
The Mathematical Sciences' Role in Homeland Security
Mathematical sciences play a key role in many important areas of Homeland Security including data mining and image analysis and voice recognition for intelligence analysis, encryption and decryption for intelligence gathering and computer security, detection and epidemiology of bioterriost attacks to determine their scope, and data fusion to analyze information coming from simultaneously from several sources. This report presents the results of a workshop focusing on mathematical methods and techniques for addressing these areas. The goal of the workshop is to help mathematical scientists and policy makers understand the connections between mathematical sciences research and these homeland security applications.
Frontiers
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Fundamental Papers in Wavelet Theory
This book traces the prehistory and initial development of wavelet theory, a discipline that has had a profound impact on mathematics, physics, and engineering. Interchanges between these fields during the last fifteen years have led to a number of advances in applications such as image compression, turbulence, machine vision, radar, and earthquake prediction. This book contains the seminal papers that presented the ideas from which wavelet theory evolved, as well as those major papers that developed the theory into its current form. These papers originated in a variety of journals from different disciplines, making it difficult for the researcher to obtain a complete view of wavelet theory and its origins. Additionally, some of the most significant papers have heretofore been available only in French or German. Heil and Walnut bring together these documents in a book that allows researchers a complete view of wavelet theory's origins and development.
Coping with Complexity: Model Reduction and Data Analysis
This volume contains the extended version of selected talks given at the international research workshop "Coping with Complexity: Model Reduction and Data Analysis", Ambleside, UK, August 31 – September 4, 2009. The book is deliberately broad in scope and aims at promoting new ideas and methodological perspectives. The topics of the chapters range from theoretical analysis of complex and multiscale mathematical models to applications in e.g., fluid dynamics and chemical kinetics.
Pattern Recognition Using Neural and Functional Networks
Biologically inspiredcomputing isdi?erentfromconventionalcomputing.Ithas adi?erentfeel; often the terminology does notsound like it’stalkingabout machines.The activities ofthiscomputingsoundmorehumanthanmechanistic as peoplespeak ofmachines that behave, react, self-organize,learn, generalize, remember andeven to forget.Much ofthistechnology tries to mimic nature’s approach in orderto mimicsome of nature’s capabilities.They havearigorous, mathematical basisand neuralnetworks forexamplehaveastatistically valid set on which the network istrained. Twooutlinesaresuggestedasthepossibletracksforpatternrecognition.They are neuralnetworks andfunctionalnetworks.NeuralNetworks (many interc- necte...
Chaos and Order in the Capital Markets
The latest developments in chaos theory - from an industry expert Chaos and Order in the Capital Markets was the first book to introduce and popularize chaos as it applies to finance. It has since become the classic source on the topic. This new edition is completely updated to include the latest ripples in chaos theory with new chapters that tie in today's hot innovations, such as fuzzy logic, neural nets, and artificial intelligence. Critical praise for Peters and the first edition of Chaos and Order in the Capital Markets "The bible of market chaologists." - BusinessWeek "Ed Peters has written a first-class summary suitable for any investment professional or skilled investor." - Technical...
The New Era in American Mathematics, 1920–1950
"The 1920s witnessed the birth of a serious mathematical research community in America. Prior to this, mathematical research was dominated by scholars based in Europe-but World War I had made the importance of scientific and technological development clear to the American research community, resulting in the establishment of new scientific initiatives and infrastructure. Physics and chemistry were the beneficiaries of this renewed scientific focus, but the mathematical community also benefitted, and over time, began to flourish. Over the course of the next two decades, despite significant obstacles, this constellation of mathematical researchers, programs, and government infrastructure would...
Noise Reduction by Wavelet Thresholding
Wavelet methods have become a widely spread tool in signal and image process ing tasks. This book deals with statistical applications, especially wavelet based smoothing. The methods described in this text are examples of non-linear and non parametric curve fitting. The book aims to contribute to the field both among statis ticians and in the application oriented world (including but not limited to signals and images). Although it also contains extensive analyses of some existing methods, it has no intention whatsoever to be a complete overview of the field: the text would show too much bias towards my own algorithms. I rather present new material and own insights in the questions involved w...
