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Neural networks and statistical learning

Author: K -L Du; M N S Swamy
Publisher: London : Springer, ©2014.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five  Read more...
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Genre/Form: Electronic books
Ebook
Additional Physical Format: Print version:
Du, K.-L.
Neural networks and statistical learning.
London : Springer, ©2014
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: K -L Du; M N S Swamy
ISBN: 9781447155713 1447155718
OCLC Number: 869904552
Description: 1 online resource (xxvii, 824 pages)
Contents: 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.
Responsibility: Ke-Lin Du, M.N.S. Swamy.

Abstract:

Inclusive coverage of all the essential neural network applications in a statistical learning framework makes this a baseline text for students and researchers, with 25 chapters on all the major  Read more...

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"Neural networks and statistical learning, has a lot to contribute. This comprehensive, well-organized and up-to-date text proves that the subject matter is richer when the topics of neural networks Read more...

 
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