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.