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Titlebook: Artificial Neural Networks; International Worksh Alberto Prieto Conference proceedings 1991 Springer-Verlag Berlin Heidelberg 1991 Artifici

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0302-9743 ries and neural models - Biological perspectives -Neural network architectures andalgorithms - Softwaredevelopments and tools - Hardware implementations -Applications.978-3-540-54537-8978-3-540-38460-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Cooperative computing and neural networks,entities enable self-organization of the system with emergent properties of associative memory, abstraction and generalization. Therefore, it should not be surprising that the mathematical tools of irreversible thermodynamics and evolution are very relevant and useful in the analysis of these intere
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Neural network modelling by means of networks of finite automata,ction (output) to an external stimulus (input), to be represented uniquely by the spatio-temporal, dynamic activation process which occurs in the network caused by the external stimulus. For a restricted class of activation processes, we are able to determine the resultant activation process caused
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Stability measurement criterion for neural networks of competitive learning,resented. With it the number of iterations needed so that the network reaches a stable configuration is reduced to a high degree. The new convergence criterion is based on the network stability measurement in contrast to the weight variation which is defined by Rumelhart et al. Results obtained in a
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