| Document Type
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BL
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| Record Number
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1017656
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| Doc. No
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b772026
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| Main Entry
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Fine, Terrence L.
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| Title & Author
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Feedforward neural network methodology /\ Terrence L. Fine.
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| Publication Statement
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New York :: Springer,, ©1999.
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| Series Statement
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Statistics for engineering and information science
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| Page. NO
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1 online resource (xvi, 340 pages) :: illustrations
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| ISBN
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0387226494
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: 1280010592
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: 6610010595
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: 9780387226491
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: 9781280010590
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: 9786610010592
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0387987452
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9780387987453
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| Bibliographies/Indexes
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Includes bibliographical references (pages 309-327) and index.
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| Contents
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Cover -- Preface -- Table of Contents -- List of Figures -- 1. Objectives, Motivation, Background, and Organization -- 2. Perceptrons-Networks with a Single Node -- 3. Feedforward Networks I: Generalities and LTU Nodes -- 4. Feedforward Networks II: Real-Valued Nodes -- 5. Algorithms for Designing Feedforward Networks -- 6. Architecture Selection and Penalty Terms -- 7. Generalization and Learning -- Appendix A -- A Note on Use as a Text -- References.
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| Abstract
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This monograph provides a thorough and coherent introduction to the mathematical properties of feedforward neural networks and to the computationally intensive methodology that has enabled their highly successful application to complex problems of pattern classification, forecasting, regression, and nonlinear systems modeling. The reader is provided with the information needed to make practical use of the powerful modeling and design tool of feedforward neural networks, as well as presented with the background needed to make contributions to several research frontiers. This work is therefore of interest to those in electrical engineering, operations research, computer science, and statistics who would like to use nonlinear modeling of stochastic phenomena to treat problems of pattern classification, forecasting, signal processing, machine intelligence, and nonlinear regression. T.L. Fine is Professor of Electrical Engineering at Cornell University.
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| Subject
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Feedforward control systems.
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| Subject
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Neural networks (Computer science)
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| Subject
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Réseaux neuronaux (Informatique)
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| Subject
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COMPUTERS-- Neural Networks.
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| Subject
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Feedforward control systems.
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| Subject
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Neural networks (Computer science)
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| Dewey Classification
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006.3/2
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| LC Classification
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QA76.87.F56 1999eb
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