Téléchargez le livre : Sensitivity Analysis for Neural Networks

Sensitivity Analysis for Neural Networks

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Éditeur :

Springer


Collection :

Natural Computing Series

Paru le : 2009-11-09

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Description
Artificial neural networks are used to model systems that receive inputs and produce outputs. The relationships between the inputs and outputs and the representation parameters are critical issues in the design of related engineering systems, and sensitivity analysis concerns methods for analyzing these relationships. Perturbations of neural networks are caused by machine imprecision, and they can be simulated by embedding disturbances in the original inputs or connection weights, allowing us to study the characteristics of a function under small perturbations of its parameters. This is the first book to present a systematic description of sensitivity analysis methods for artificial neural networks. It covers sensitivity analysis of multilayer perceptron neural networks and radial basis function neural networks, two widely used models in the machine learning field. The authors examine the applications of such analysis in tasks such as feature selection, sample reduction, and network optimization. The book will be useful for engineers applying neural network sensitivity analysis to solve practical problems, and for researchers interested in foundational problems in neural networks.
Pages
86 pages
Collection
Natural Computing Series
Parution
2009-11-09
Marque
Springer
EAN papier
9783642025310
EAN EPUB
9783642025327
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
8
Taille du fichier
973 Ko
Prix
94,94 €

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