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020 _a9783319223032
024 7 _a10.1007/978-3-319-22303-2
_2doi
040 _aES-MaUEC
050 4 _aQA403.3
_b.A94 2016 EB
082 0 4 _a621.382
100 1 _aAverbuch, Amir
_d1947-
_0n 88668014
_948566
245 1 0 _aSpline and Spline Wavelet Methods with Applications to Signal and Image Processing :
_bVolume II: Non-Periodic Splines
_cby Amir Z Averbuch, Pekka Neittaanmäki, Valery A Zheludev
250 _a1st ed.
264 1 _aCham
_bSpringer International Publishing
_c2016
300 _a1 recurso en línea (XXV, 426 p.)
_b129 ilustraciones, 87 ilustraciones en color
336 _aTexto (visual)
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
505 0 _aPreface.-1 Introduction: Signals and Transforms -- 2 Introduction: Digital Filters and Filter Banks -- 3 Mixed Convolutions and Zak Transforms -- 4 Non-Periodic Polynomial Splines -- 5 Quasi-Interpolating and Smoothing Local Splines -- 6 Cubic Local Splines on Non-Uniform Grid -- 7 Splines Computation by Subdivision -- 8 Polynomial Spline-Wavelets -- 9 Non-Periodic Discrete Splines -- 10 Non-Periodic Discrete-Spline Wavelets -- 11 Biorthogonal Wavelet Transforms -- 12 Biorthogonal Wavelet Transforms Originating from Splines -- 13 Data Compression Using Wavelet and Local Cosine Transforms -- 14 Wavelet Frames Generated by Perfect Reconstruction Filter Banks -- 15 Biorthogonal Multiwavelets Originated from Hermite Splines -- 16 Multiwavelet Frames Originated from Hermite Splines -- Appendix A - Guide to Spline SoftN -- Glossary -- Index.
520 3 _aThis book presents various contributions of splines to signal and image processing from a unified perspective that is based on the Zak transform (ZT). It expands the methodology from periodic splines, which were presented in the first volume, to non-periodic splines. Together, these books provide a universal toolbox accompanied by MATLAB software for manipulating polynomial and discrete splines, spline-based wavelets, wavelet packets and wavelet frames for signal/ image processing applications. In this volume, we see that the ZT provides an integral representation of discrete and polynomial splines, which, to some extent, is similar to Fourier integral. The authors explore elements of spline theory and design, and consider different types of polynomial and discrete splines. They describe applications of spline-based wavelets to data compression. These splines are useful for real-time signal processing and, in particular, real-time wavelet and frame transforms. Further topics addressed in this volume include: "global" splines, such as interpolating, self-dual and smoothing, whose supports are infinite; the compactly supported quasi-interpolating and smoothing splines including quasi-interpolating splines on non-uniform grids; and cubic Hermite splines as a source for the design of multiwavelets and multiwavelet frames. Readers from various disciplines including engineering, computer science and mathematical information technology will find the descriptions of algorithms, applications and software in this book especially useful.
650 7 _aWavelets (Matemáticas)
_0comprobar BNE20030953580
_2embne
_9161271
650 7 _aGráficos de ordenador
_0comprobar BNE19900994608
_2embne
_9141143
650 7 _aMatemáticas discretas
_0comprobar BNE20021506428
_2embne
_9160233
700 1 _aNeittaanmak̈i, P. (Pekka)
_0n 83149130
_948567
700 1 _aZheludev, Valery A.
_0nb2014013123
_948569
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-22303-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9783319223032
907 _a.b12941050
_b04-11-17
_c21-11-16
942 _2lcc
_cLE
945 _aQA403.3 .A94 2016 EB
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