A neural network module with pretuning for search and reproduction of input-output mapping

Authors:
Igor Shepelev
Affiliations:
A.B. Kogan Research Institute for Neurocybernetics, Rostov State University
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Year:
2006

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Abstract

A neural network that uses a pretuning procedure for function approximation is presented. Unlike traditional neural network algorithms in which changeable parameters are multiplicative weights of connections between neurons in the network, the pretuning procedure deals with additive thresholds of interneurons of the proposed neural network and is a dynamical combinatory inhibition of these neurons. It is shown that in this case the neural network can combine local approximation and distributed activation. The usefulness of the neural network with pretuning (NNP) for the tasks of search and reproduction of sensorimotor mapping of robot is briefly discussed.