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Fundamentals of Wavelets - D. Jizheng

Fundamentals of Wavelets

(Autor)

Buch | Hardcover
274 Seiten
2011
WIT Press (Verlag)
978-1-84564-642-4 (ISBN)
CHF 269,95 inkl. MwSt
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Many researchers from various scientific disciplines use wavelets, but as often as not they fail to understand the fundamental concepts of wavelet analysis and why wavelets can be used both to solve and to treat problems. Fundamentals of Wavelets is designed to meet the needs of the above-mentioned researchers and to demonstrate that wavelets are not only the microscopes and telescopes in mathematics, but that it is also not necessary to have a detailed theoretical knowledge to use them to solve problems.

Di JIZHENG (Ph.D., Dalian University of Science and Engineering) is a professor in the Department of Applied Mathematics, College of Science, Zhejiang University of Technology, CHINA. He has served as a visiting scholar at North Dakota State University, USA. He was the chief leader of the College of Mathematics and Computer science in Shanxi Teachers University and has also served as the vice leader of Shanxi branch of Chinese Mathematics Society, vice leader of Shanxi branch of Chinese Engineering and Applied Mathematics Society, and the secretary of the Research Institute of Mathematics Education in Liberal Arts. His current research focuses on approximation theory and wavelets. He is the author of over 40 published research papers and 39 books, including one on the Principles Of Wavelets. His 16 research items were supported by foundations.

Contents 1 Mathematical preliminaries Some mathematical concepts and knowledge; Lp(R); Functions in Lp(R); Inner product space; Bases and frames in Hilbert spaces; Transformation skills of sums and integrals; Fourier series; Pointwise convergence; Average convergence; Several forms of the Fourier series; Some problems about the Fourier series; Fourier transforms; Fourier transforms and inverse transforms; Properties of the Fourier transforms; Comparison of the Fourier series and the transforms; Time - frequency window; Window Fourier transforms; Different definitions of the Fourier transforms and multivariate Fourier transforms; Sampling theorem and filtering; Sampling theorem; Mathematical representations of filtering; Filtering by use of sampling; Filters and their response functions; Associations about filters 2 Wavelet transform and its applications Wavelet transforms; Univariate wavelet transforms; The meanings of wavelet transforms; Multivariate wavelet transforms; Applications of wavelet transforms; To use wavelet transforms in filtering; Boundary drawing by using wavelet transforms 3 Multiresolution and orthogonal wavelets Multiresolution analysis; Subspace Vj and multiresolution analysis; Scaling functions; Refinement relations; Subspace Wj; Wavelet; Filter response functions and their applications; Filter response functions H, G; The proof of the main theorem in wavelet analysis; A method to construct wavelets; Effects of filters - Mallat algorithms; Low pass and high pass; Decomposition algorithms; Reconstruction algorithms; Regularity and vanishing moments of wavelets; Regularity; Vanishing moments; Relationship of regularities and vanishing moments; Wavelets are telescopes and microscopes in mathematics 4 Compactly supported real wavelets Some relative questions; Forms of finite-sum refinement relations; Approximate calculations; Constructions of compactly supported wavelets; Relative prepare knowledge; Constructions of real-valued wavelets; Decomposition and reconstruction algorithms; Mallat algorithms; Sampling algorithms; Wavelet packet analysis; Wavelet packet decompositions; {un}and space; Decompositions of Wj, Vj; The equal-dilatation property; Wavelet storehouses; Choices of the best wavelet packet bases; Best wavelet packet bases; Cost functions; Method to choose the best wavelet packet bases; Algorithms; Decomposition algorithms; Reconstruction algorithms 6 Multivariate wavelets Principles of multivariate wavelets to deal with problems; Bivariate multiresolution analysis; Mallat algorithms; Sampling algorithms 7 Biorthogonal wavelets Constructions and algorithms; Constructions of biorthogonal wavelets; Algorithms of biorthogonal wavelets; Compactly supported biorthogonal real wavelets; Compactly supported biorthogonal real wavelets; Symmetric or antisymmetric real wavelets 8 Spline wavelets Simple introductions of splines; Splines of order m; B-splines of order m; Constructions of spline wavelets; Non-compactly supported orthogonal spline wavelets; Compactly supported semiorthogonal symmetric or antisymmetric spline wavelets; Non-compactly supported semiorthogonal symmetric or antisymmetric spline wavelets; Single compactly supported biorthogonal symmetric or antisymmetric spline wavelets 9 The lifting theory of biorthogonal wavelets Principles of the lifting theory of biorthogonal wavelets; Algorithms of lifted biorthogonal wavelets; Examples of choices of lifting filters; A direct method to construct biorthogonal wavelets Bibliography

Erscheint lt. Verlag 16.12.2011
Zusatzinfo Illustrations
Verlagsort Southampton
Sprache englisch
Maße 156 x 234 mm
Themenwelt Mathematik / Informatik Mathematik Analysis
Naturwissenschaften
ISBN-10 1-84564-642-8 / 1845646428
ISBN-13 978-1-84564-642-4 / 9781845646424
Zustand Neuware
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