The past two decades have seen an explosion of renewed interest in the areas of Artificial Intelligence and

Information Processing. Much of this interest has come about with the successful demonstration of real-world

applications of Artificial Neural Networks (ANNs) and their ability to learn. Initially proposed during the

1950s, the technology suffered a roller coaster development accompanied by exaggerated claims of their

virtues, excessive competition between rival research groups, and the perils of boom and bust research

funding. ANNs have only recently found a reasonable degree of respectability as a tool suitable for achieving

a nonlinear mapping between an input and output space. ANNs have proved particularly valuable for

applications where the input data set is of poor quality and not well characterized. At this stage, pattern

recognition and control systems have emerged as the most successful ANN applications.