The recent resurgence of interest in neural net works has its roots in the recognition that the brain performs computations in a different manner than do conventional digital computers. Computers are extremely tast and precise at executing sequences of instructions that have been formulated for them.

This book introduces the foundations of artificial neural systems. Much of the inspiration for such systems comes from neuroscience. Although the newly developed paradigms of artificial neural networks have strongly contributed to the discovery, understanding and utilization of potential functional similarities between human and artificial information processing systems, many questions remain open. Intense research interest persists and the area continues to develop. And to achieve this research objective, it is necessary to define the focus of the study of artificial neural systems. Artificial neural systems or neural networks are physically cellular systems which can acquire, store and utilize experimental knowledge. This book focuses on the foundations of such networks. The fundamentals of artificial neural systems theory, algorithms for information acquisition and retrieval, examples of applications, and implementations issues are also included..

The purpose of this book is to help the reader understand the acquisition and retrieval of experiental knowledge in densely interconnected networks containing cells of processing elements and interconnecting links. Some of the discussed networks can be considered adaptive; others acquire knowledge a priori. Retrieval of knowledge is termed by some authors as neural computation. However, "neural computation is only a segment of the artificial neural systems focus. This book also addresses the concepts of parallel machines that are able to acquire knowledge, and the corresponding issues of implementation.

This book is written at a comprehensible level for the professional and students who have had calculus, linear algebra, analytical geometry, differential equations, and some exposure to optimization theory. Due to the emphasis on systems, the book should be appropriate for electrical, computer, industrial, mechanical and manufacturing engineering professionals and students as well as for computer and information science, physics and mathematics professionals.

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