Multiobjective RBFNNs designer for function approximation: an application for mineral reduction
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Application of ANOVA to a cooperative-coevolutionary optimization of RBFNs
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
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We study the macroscopic dynamics of a three-state mean-field neural network, by using information theory principles. The results are expressed in terms of the relevant order parameters of the system, The network is composed by bilinear and biquadratic synaptic interactions, which yields an improvement of the storage and information properties of the network, measured by the mutual information and the basins of attraction. The introduction of a self-adaptive mechanism in the synapses is analyzed. The coexistence of the usual retrieval phase with a quadrupolar phase, as well as with a new informative anti-quadrupolar phase, is observed.