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Avis sur Feedforward Neural Network Methodology de Terrence L Fine Format Relié - Livre Littérature Générale
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Présentation Feedforward Neural Network Methodology de Terrence L Fine Format Relié
- Livre Littérature Générale
Résumé :
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.
Sommaire:
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.
From the reviews: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION ...Fine must be congratulated for a coherent presentation of carefully selected material. Given the diversity of the field, this represented a serious challenge. Again, Feeforward Neural Network Methodlogy is an excellent reference for whoever wants to be brought to the frontier of research. I enthusiastically recommend it.
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