Designed as an introductory level textbook on artificial neural networks at the postgraduate and senior undergraduate levels in any branch of engineering, this self-contained and well-organized book highlights the need for new models of computing based on the fundamental principles of neural networks. Professor yegnanarayana compresses, into the covers of a single volume, his several years of rich experience, in teaching and research in the areas of speech processing, image processing, artificial intelligence and neural networks. He gives a masterly analysis of such topics as basics of artificial neural networks, functional units of artificial neural networks for pattern recognition tasks, feedforward and feedback neural networks, and architectures for complex pattern recognition tasks. Throughout, the emphasis is on the pattern processing feature of the neural networks. Besides, the presentation of real-world applications provides a practical thrust to the discussion. About the auhtor dr. B.yegnanarayana is professor in department of computer science and engineering, indian institute of technology madras. A fellow of the indian national academy of engineers, prof. Yegnanarayana has published several papers in reputed national and international journals. His areas of interest include signal processing, speech and image processing, and neural networks. Table of contents preface acknowledgements introduction basics of artificial neural networks activation and synaptic dynamics functional units of ann for pattern recognition tasks feedforward neural networks feedback neural networks competitive learning neural networks architectures for complex pattern recognition tasks applications of ann appendices bibliography author index subject index ...