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Neural networks and statistical learning
~
Du, Ke-Lin.
Neural networks and statistical learning
Record Type:
Electronic resources : Monograph/item
Title/Author:
Neural networks and statistical learningby Ke-Lin Du, M. N. S. Swamy.
Author:
Du, Ke-Lin.
other author:
Swamy, M. N. S.
Published:
London :Springer London :2019.
Description:
xxx, 988 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Pattern perception.
Online resource:
https://doi.org/10.1007/978-1-4471-7452-3
ISBN:
9781447174523$q(electronic bk.)
Neural networks and statistical learning
Du, Ke-Lin.
Neural networks and statistical learning
[electronic resource] /by Ke-Lin Du, M. N. S. Swamy. - 2nd ed. - London :Springer London :2019. - xxx, 988 p. :ill. (some col.), digital ;24 cm.
Introduction -- Fundamentals of Machine Learning -- Perceptrons -- Multilayer perceptrons: architecture and error backpropagation -- Multilayer perceptrons: other learing techniques -- Hopfield networks, simulated annealing and chaotic neural networks -- Associative memory networks -- Clustering I: Basic clustering models and algorithms -- Clustering II: topics in clustering -- Radial basis function networks -- Recurrent neural networks -- Principal component analysis -- Nonnegative matrix factorization and compressed sensing -- Independent component analysis -- Discriminant analysis -- Support vector machines -- Other kernel methods -- Reinforcement learning -- Probabilistic and Bayesian networks -- Combining multiple learners: data fusion and emsemble learning -- Introduction of fuzzy sets and logic -- Neurofuzzy systems -- Neural circuits -- Pattern recognition for biometrics and bioinformatics -- Data mining.
ISBN: 9781447174523$q(electronic bk.)
Standard No.: 10.1007/978-1-4471-7452-3doiSubjects--Topical Terms:
182522
Pattern perception.
LC Class. No.: Q342 / .D855 2019
Dewey Class. No.: 006.3
Neural networks and statistical learning
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by Ke-Lin Du, M. N. S. Swamy.
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2019.
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xxx, 988 p. :
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ill. (some col.), digital ;
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24 cm.
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Introduction -- Fundamentals of Machine Learning -- Perceptrons -- Multilayer perceptrons: architecture and error backpropagation -- Multilayer perceptrons: other learing techniques -- Hopfield networks, simulated annealing and chaotic neural networks -- Associative memory networks -- Clustering I: Basic clustering models and algorithms -- Clustering II: topics in clustering -- Radial basis function networks -- Recurrent neural networks -- Principal component analysis -- Nonnegative matrix factorization and compressed sensing -- Independent component analysis -- Discriminant analysis -- Support vector machines -- Other kernel methods -- Reinforcement learning -- Probabilistic and Bayesian networks -- Combining multiple learners: data fusion and emsemble learning -- Introduction of fuzzy sets and logic -- Neurofuzzy systems -- Neural circuits -- Pattern recognition for biometrics and bioinformatics -- Data mining.
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Pattern perception.
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Computational intelligence.
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Neural networks (Computer science)
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Engineering.
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Data mining.
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Optical pattern recognition.
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Mathematical Models of Cognitive Processes and Neural Networks.
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Computational Intelligence.
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Artificial Intelligence.
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Pattern Recognition.
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Signal, Image and Speech Processing.
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Swamy, M. N. S.
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https://doi.org/10.1007/978-1-4471-7452-3
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Mathematics and Statistics (Springer-11649)
based on 0 review(s)
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電子館藏
Items
1 records • Pages 1 •
1
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000000176258
電子館藏
1圖書
電子書
EB Q342 .D812 2019 2019
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1 records • Pages 1 •
1
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https://doi.org/10.1007/978-1-4471-7452-3
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