Artificial Neural Network Modelling (Studies in by Subana Shanmuganathan, Sandhya Samarasinghe

By Subana Shanmuganathan, Sandhya Samarasinghe

This ebook covers theoretical facets in addition to contemporary cutting edge functions of synthetic Neural networks (ANNs) in common, environmental, organic, social, commercial and automatic systems.

It offers contemporary result of ANNs in modelling small, huge and complicated structures less than 3 different types, specifically, 1) Networks, constitution Optimisation,  Robustness and Stochasticity 2) Advances in Modelling organic and Environmental Systems and three) Advances in Modelling Social and financial Systems.  The ebook goals at serving undergraduates, postgraduates and researchers in ANN computational modelling.    

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The training algorithms employed and the difficulty of the pattern recognition problem tested are key factors determining the impact of perturbations. The results show that certain perturbations, such as neuron splitting and scaling, can achieve memory persistence by functional recovery of lost patterning information. The study of models integrating both growth and reduction, combined with distributed information processing is an essential first step for a computational theory of pattern formation, plasticity, and robustness.

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