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005 20170628034531.0
007 cr nn 008mamaa
008 100301s2007 gw | s |||| 0|eng d
020 _a9783540361220
_9978-3-540-36122-0
024 7 _a10.1007/978-3-540-36122-0
_2doi
050 4 _aTA329-348
050 4 _aTA640-643
072 7 _aTBJ
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aChen, Ke.
_eeditor.
245 1 0 _aTrends in Neural Computation
_h[electronic resource] /
_cedited by Ke Chen, Lipo Wang.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2007.
300 _aX, 512 p. 159 illus. Also available online.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v35
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.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aWang, Lipo.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540361213
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v35
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-36122-0
912 _aZDB-2-ENG
999 _c20311
_d20311