Analysis and Applications of Artificial Neural Networks [Scan.] by L. Veelenturf [Repost]

Thorough, compact, and self-contained, this explanation and analysis of a broad range of neural nets is conveniently structured so that readers can first gain a quick global understanding of neural nets – "without" the mathematics – and can then delve into mathematical specifics as necessary. The behavior of neural nets is first explained from an intuitive perspective; the formal analysis is then presented; and the practical implications of the formal analysis are stated separately. Analyzes the behavior of the six main types of neural networks – The Binary Perceptron, The Continuous Perceptron (Multi-Layer Perceptron), The Bidirectional Memories, The Hopfield Network (Associative Neural Nets), The Self-Organizing Neural Network of Kohonen, and the new Time Sequentional Neural Network.