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. For technically-oriented individuals working with information retrieval, pattern recognition, speech recognition, signal processing, data classification.
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This volume is an analysis of the behaviour of the three types of neural networks: the binary perceptron, the continuous perceptron and the self-organizing neural network. Analysis is largely mathematical but concepts are also explained through practical examples.
"About this title" may belong to another edition of this title.
Book Description Prentice Hall, 1995. Textbook Binding. Book Condition: New. Bookseller Inventory # DADAX013489832X
Book Description Prentice Hall, 1995. Textbook Binding. Book Condition: Brand New. 1st edition. 368 pages. 9.75x7.25x0.75 inches. In Stock. Bookseller Inventory # 013489832X