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001 288679
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008 150903s2013 xxu| o |||| 0|eng d
020 _a9781461441069
_99781461441069
024 7 _a10.1007/9781461441069
_2doi
035 _avtls000341205
039 9 _a201509030834
_bVLOAD
_c201405050225
_dVLOAD
_y201402061053
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTK5102.9
100 1 _aDiniz, Paulo S. R.
_eautor
_9304207
245 1 0 _aAdaptive Filtering :
_bAlgorithms and Practical Implementation /
_cby Paulo S. R. Diniz.
250 _a4th ed. 2013.
264 1 _aBoston, MA :
_bSpringer US :
_bImprint: Springer,
_c2013.
300 _axxI, 652 páginas 199 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 _aIntroduction to Adaptive Filtering -- Fundamentals of Adaptive Filtering -- The Least-Mean-Square (LMS) Algorithm -- LMS-Based Algorithms -- Conventional RLS Adaptive Filter -- Data-Selective Adaptive Filtering -- Adaptive Lattice-Based RLS Algorithms -- Fast Transversal RLS Algorithms -- QR-Decomposition-Based RLS Filters -- Adaptive IIR Filters -- Nonlinear Adaptive Filtering -- Subband Adaptive Filters -- Blind Adaptive Filtering.
520 _aIn the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes of adaptive filtering algorithms are presented in a unified framework, using clear notations that facilitate actual implementation. The main algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Many examples address problems drawn from actual applications. New material to this edition includes: Analytical and simulation examples in Chapters 4, 5, 6 and 10 Appendix E, which summarizes the analysis of set-membership algorithm Updated problems and references Providing a concise background on adaptive filtering, this book covers the family of LMS, affine projection, RLS and data-selective set-membership algorithms as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Several problems are included at the end of chapters, and some of these problems address applications. A user-friendly MATLAB package is provided where the reader can easily solve new problems and test algorithms in a quick manner. Additionally, the book provides easy access to working algorithms for practicing engineers.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781461441052
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4614-4106-9
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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