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008			150903s2011 gw | o |||| 0|eng d
020			_a9783642198267 _99783642198267
024	7		_a10.1007/9783642198267 _2doi
035			_avtls000356726
039		9	_a201509030548 _bVLOAD _c201405060409 _dVLOAD _y201402191300 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQ342
100	1		_aAnastassiou, George A. _eautor _9305487
245	1	0	_aTowards Intelligent Modeling: Statistical Approximation Theory / _cby George A. Anastassiou, Oktay Duman.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2011.
300			_axvI, 236 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aIntelligent Systems Reference Library, _x1868-4394 ; _v14
500			_aSpringer eBooks
505	0		_a Introduction -- Statistical Approximation by Bivariate Picard Singular Integral Operators -- Uniform Approximation in Statistical Sense by Bivariate Gauss-Weierstrass Singular Integral Operators -- Statistical Lp-Convergence of Bivariate Smooth Picard Singular Integral Operators -- Statistical Lp-Approximation by Bivariate Gauss-Weierstrass Singular Integral Operators -- A Baskakov-Type Generalization of Statistical Approximation Theory -- Weighted Approximation in Statistical Sense to Derivatives of Functions -- Statistical Approximation to Periodic Functions by a General Family of Linear Operators -- Relaxing the Positivity Condition of Linear Operators in Statistical Korovkin Theory -- Statistical Approximation Theory for Stochastic Processes -- Statistical Approximation Theory for Multivariate Stochas tic Processes.
520			_aThe main idea of statistical convergence is to demand convergence only for a majority of elements of a sequence. This method of convergence has been investigated in many fundamental areas of mathematics such as: measure theory, approximation theory, fuzzy logic theory, summability theory, and so on. In this monograph we consider this concept in approximating a function by linear operators, especially when the classical limit fails. The results of this book not only cover the classical and statistical approximation theory, but also are applied in the fuzzy logic via the fuzzy-valued operators. The authors in particular treat the important Korovkin approximation theory of positive linear operators in statistical and fuzzy sense. They also present various statistical approximation theorems for some specific real and complex-valued linear operators that are not positive. This is the first monograph in Statistical Approximation Theory and Fuzziness. The chapters are self-contained and several advanced courses can be taught. The research findings will be useful in various applications including applied and computational mathematics, stochastics, engineering, artificial intelligence, vision and machine learning. This monograph is directed to graduate students, researchers, practitioners and professors of all disciplines.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aDuman, Oktay. _eautor _9317354
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783642198250
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-642-19826-7 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c302585 _d302585