With applications in pattern recognition, data compression and numerical analysis, the wavelet transform is a key area of modern mathematics that brings new approaches to the analysis and synthesis of signals. This book presents the central issues and emphasizes comparison, assessment and how to combine method and application. It reviews different approaches to guide researchers to appropriate classes of techniques.Includes exercises, solutions and an itinerary for readers interested in algorithms and applications.-- Includes further reading suggestions in each chapter.
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This book presents the central issues and emphasizes comparison, assessment and how to combine method and application. It reviews different approaches to guide researchers to appropriate classes of techniques. Includes exercises and solutions and gives an itinerary for readers interested in algorithms and the applications.
A. K. Louis, Universität des Saarlandes, Germany P. Maass, Universität Potsdam, Germany A. Rieder, Universität des Saarlandes, Germany Wavelets have in recent years brought new approaches to the areas of analysis and synthesis of signals, a few examples of which include pattern recognition, data compression, numerical analysis, quantum field theory and acoustics. In this book the authors take the reader through both the theory of wavelets and their applications. Chapter one is devoted to the theoretical background of the wavelet transform and to some of its properties, moving on to the discrete transform. The second chapter addresses the functions of wavelets within mathematics and their construction is introduced. Finally, chapter three presents a selection of the broad variety of applications of wavelets, including examples from signal analysis, quality control, data compression in digital image processing, the regularlization of ill posed problems and numerical analysis of boundary value problems. This book provides an invaluable resource for researchers and professionals in applied mathematics, particularly in numerical analysis and signal processing, as well as for engineers and physicists with a strong mathematical background. Contents Notations Introduction
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