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130125s2013 gw | s |||| 0|eng d |
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|a 9783642348167
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7 |
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|a 10.1007/978-3-642-34816-7
|2 doi
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|a Sistema de Bibliotecas del Tecnológico de Costa Rica
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|a Liu, Jinkun.
|e author.
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|a Radial Basis Function (RBF) Neural Network Control for Mechanical Systems :
|b Design, Analysis and Matlab Simulation /
|c by Jinkun Liu.
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250 |
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|a 1st ed. 2013.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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|a XV, 365 p. :
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Introduction -- RBF Neural Network Design and Simulation -- RBF Neural Network Control Based on Gradient Descent Algorithm -- Adaptive RBF Neural Network Control -- Neural Network Sliding Mode Control -- Adaptive RBF Control Based on Global Approximation -- Adaptive Robust RBF Control Based on Local Approximation -- Backstepping Control with RBF -- Digital RBF Neural Network Control -- Discrete Neural Network Control -- Adaptive RBF Observer Design and Sliding Mode Control.
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|a Control engineering.
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|a Vibration.
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|a Dynamical systems.
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|a Dynamics.
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|a Computational intelligence.
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|a Neural networks (Computer science) .
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|a Control and Systems Theory.
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|a Vibration, Dynamical Systems, Control.
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4 |
|a Computational Intelligence.
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4 |
|a Mathematical Models of Cognitive Processes and Neural Networks.
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|a SpringerLink (Online service)
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|t Springer eBooks
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