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020 _a9781461441458
_99781461441458
024 7 _a10.1007/9781461441458
_2doi
035 _avtls000341218
039 9 _a201509030834
_bVLOAD
_c201405050225
_dVLOAD
_y201402061054
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040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTK5102.9
100 1 _aShen, Xiaoping.
_eeditor.
_9318778
245 1 0 _aMultiscale Signal Analysis and Modeling /
_cedited by Xiaoping Shen, Ahmed I. Zayed.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _axvii, 378 páginas 88 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
505 0 _aPart I Sampling -- Convergence and Summability of Cardinal Series -- Improved Approximation via Use of Transformations -- Generalized Sampling In L2(Rd) Shift-Invariant Subspaces With Multiple Stable Generators -- Function Spaces for Sampling Expansions -- Coprime Sampling And Arrays In One And Multiple Dimensions -- Chromatic Expansions and the Bargmann Transform -- Representation formulas for Hardy space functions through the Cuntz relations and new interpolation problems -- Constructions and a generalization of perfect autocorrelation sequences on Z -- Part II Multiscale Analysis -- A unified theory for multiscale analysis of complex time series -- Wavelet Analysis of ECG Signals -- Multiscale signal processing with discrete Hermite functions -- Local Discriminant Basis Using Earth Mover's Distance Earth Mover’s Distance Based Local Discriminant Basis -- Part III statistical Analysis -- Characterizations of Certain Continuous Distributions -- Bayesian Wavelet Shrinkage Strategies - A Review -- Multi-parameter regularization for construction of extrapolating estimators in  statistical learning theory.
520 _aMultiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image processing using Local Discriminant Basis (LDB) Develops multi-parameter regularized extrapolating estimators in statistical learning theory Multiscale Signal Analysis and Modeling is an ideal book for graduate students and practitioners, especially those working in or studying the field of signal/image processing, telecommunication and applied statistics. It can also serve as a reference book for engineers, researchers and educators interested in mathematical and statistical modeling. 
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aZayed, Ahmed I.
_eeditor.
_9307151
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781461441441
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4614-4145-8
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c288843
_d288843