Computer aided investigations of artificial neural systems

Abstract

An attempt is made to demonstrate how symbolic computation can be applied to aid in the analysis and derivation of neural systems. The authors review the general method and techniques of the Lyapunov method for the stability analysis of artificial neural systems. They present some strategies for using computer algebra systems and their extensions to analyze the stability of known neural systems and to derive novel stable ones. A brief description of a toolkit developed in MACSYMA is also provided. An illustration is given to sketch the derivation of neural learning dynamics by the toolkit. A discussion of future developments is included.<>