Feedforward neural network methodology
著者
書誌事項
Feedforward neural network methodology
（Statistics for engineering and information science）
Springer, c1999
- : hardcover
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注記
Includes bibliographical references (p. [309]-327) and index
内容説明・目次
内容説明
This decade has seen an explosive growth in computational speed and memory and a rapid enrichment in our understanding of artificial neural networks. These two factors provide systems engineers and statisticians with the ability to build models of physical, economic, and information-based time series and signals. This book provides a thorough and coherent introduction to the mathematical properties of feedforward neural networks and to the intensive methodology which has enabled their highly successful application to complex problems.
目次
Objectives, Motivation, Background, and Organization.- Perceptions-Networks with a Single Node.- Feedforward Networks I: Generalities and LTU Nodes.- Feedforward Networks II: Real-Valued Nodes.- Algorithms for Designing Feedforward Networks.- Architecture Selection and Penalty Terms.- Generalization and Learning.
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