| 1,Introduction
2,Learning processes 3,single layer perceptrons 4,Multiayer perceptrons 5,Redial-Basis function networks 6,support vector machines 7,committee machines 8,principal components Analysis 9,self-organizing maps 10,information-theoretic models 11,stochastic machines and their approximates rooted in statistical mechanics 12,Neurodynamic programming 13,Temporal processing using feedforward networks 14,neurodynamics 15,Dynamically driven recurrent networks |
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