Neural networks represent a technology rooted in several disciplines. Reflecting this multidisciplinary nature of the subject, this well-organized text provides a comprehensive foundation to neural networks. Its extensive state-of-the-art coverage helps readers realize the tremendous potential and possibilities of neural networks. Following a brief introduction to the properties and composition of neural networks, the text describes the learning machines of neural networks, such as multilayer perceptrons, back-propagation algorithm, radial-basis function networks, and details all the intricacies of learning processes such as Hebbian learning, information theory, dynamic programming and its relationship with reinforcement learning, substantiating the key concepts with relevant worked-out examples and illustrations. Finally, the book concludes with an epilogue that briefly describes the role of neural networks in the construction of intelligent machines for pattern recognition, control, and signal processing. Table of Contents Preface. Acknowledgments. Abbreviations and Symbols. 1. Introduction. 2. Learning Processes. 3. Single Layer Perceptrons. 4. Multilayer Perceptrons. 5. Radial-Basis Function Networks. 6. Support Vector Machines. 7. Committee Machines. 8. Principal Components Analysis. 9. Self-Organizing Maps. 10. Information-Theoretic Models. 11. Stochastic Machines and Their Approximates Rooted in Statistical Mechanics. 12. Neurodynamic Programming. 13. Temporal Processing Using Feedforward Networks. 14. Neurodynamics. 15. Dynamically Driven Recurrent Networks. Epilogue. Bibliography. Index. Special Features Fifteen computer-oriented experiments distributed throughout the book (13 of which use MATLAB) enable readers gain an understanding of the design mechanism and practical application of neural networks. Improved and expanded end-of-chapter problems are challenging in nature and help readers in self-evaluation. Chapter objectives, worked-out examples and problems make the text more comprehensible. Photographs, illustrations, a comprehensive glossary and an extensive bibliography enhance the value of the text. Primarily intended as text for students of computer science, electrical engineering and IT, it would also appeal to professionals in the field.