Author(s)

E. Eberbach

Abstract

Neural networks in the CSA model E. Eberbach Jodrey School of Computer Science, Acadia University Wolfville, Nova Scotia, Canada BOP ABSTRACT Neural Networks provide a powerful tool for new generation computers. The biggest problem of neural networks is the lack of representational power. We propose to analyze neural networks using the approach which is more general than neural networks. A Calculus of Self- modifiable Algorithms is a universal model for intelligent and parallel systems, integrating different styles of programming. and applied in different domains of future generation computers. Applying this model to neural networks gives some hints how to increase a representational power of neural networks. INTRODUCTION Neural Network processing provides a new way of thinking about perception, memory, learning and thinking [19]. Artificial Intelligence community is split be- tween advocates of powerful symbolic representations that lack efficient learning procedures, and adv

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