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001			295559
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008			150903s2007 gw | o |||| 0|eng d
020			_a9783540361220 _99783540361220
024	7		_a10.1007/9783540361220 _2doi
035			_avtls000349165
039		9	_a201509030414 _bVLOAD _c201405050343 _dVLOAD _y201402071155 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTA329-348
100	1		_aChen, Ke. _eeditor. _9329160
245	1	0	_aTrends in Neural Computation / _cedited by Ke Chen, Lipo Wang.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2007.
300			_ax, 512 páginas 159 ilustraciones Also available online. _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		_aStudies in Computational Intelligence, _x1860-949X ; _v35
500			_aSpringer eBooks
505	0		_aHyperbolic Function Networks for Pattern Classification -- Variable Selection for the Linear Support Vector Machine -- Selecting Data for Fast Support Vector Machines Training -- Universal Approach to Study Delayed Dynamical Systems -- A Hippocampus-Neocortex Model for Chaotic Association -- Latent Attractors: A General Paradigm for Context-Dependent Neural Computation -- Learning Mechanisms in Networks of Spiking Neurons -- GTSOM: Game Theoretic Self-organizing Maps -- How to Generate Different Neural Networks -- A Gradient-Based Forward Greedy Algorithm for Space Gaussian Process Regression -- An Evolved Recurrent Neural Network and Its Application -- A Min-Max Modular Network with Gaussian-Zero-Crossing Function -- Combining Competitive Learning Networks of Various Representations for Sequential Data Clustering -- Modular Neural Networks and Their Applications in Biometrics -- Performance Analysis of Dynamic Cell Structures -- Short Term Electric Load Forecasting: A Tutorial -- Performance Improvement for Formation-Keeping Control Using a Neural Network HJI Approach -- A Robust Blind Neural Equalizer Based on Higher-Order Cumulants -- The Artificial Neural Network Applied to Servo Control System -- Robot Localization Using Vision.
520			_aNowadays neural computation has become an interdisciplinary field in its own right; researches have been conducted ranging from diverse disciplines, e.g. computational neuroscience and cognitive science, mathematics, physics, computer science, and other engineering disciplines. From different perspectives, neural computation provides an alternative methodology to understand brain functions and cognitive process and to solve challenging real-world problems effectively. Trend in Neural Computation includes twenty chapters either contributed from leading experts or formed by extending well selected papers presented in the 2005 International Conference on Natural Computation. The edited book aims to reflect the latest progresses made in different areas of neural computation, including theoretical neural computation, biologically plausible neural modeling, computational cognitive science, artificial neural networks – architectures and learning algorithms and their applications in real-world problems. Researchers, graduate students and industrial practitioners in the broad areas of neural computation would benefit from the state-of-the-art work collected in this book.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aWang, Lipo. _eeditor. _9327272
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540361213
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-36122-0 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c295559 _d295559