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Neural networks and statistical learning

This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercise...

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Detalles Bibliográficos
Autores principales: Du, Ke-Lin, Swamy, M N S
Lenguaje:eng
Publicado: Springer 2019
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-1-4471-7452-3
http://cds.cern.ch/record/2691329
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author Du, Ke-Lin
Swamy, M N S
author_facet Du, Ke-Lin
Swamy, M N S
author_sort Du, Ke-Lin
collection CERN
description This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing. Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include: • multilayer perceptron; • the Hopfield network; • associative memory models; • clustering models and algorithms; • t he radial basis function network; • recurrent neural networks; • nonnegative matrix factorization; • independent component analysis; •probabilistic and Bayesian networks; and • fuzzy sets and logic. Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning.
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spelling cern-26913292021-04-21T18:19:30Zdoi:10.1007/978-1-4471-7452-3http://cds.cern.ch/record/2691329engDu, Ke-LinSwamy, M N SNeural networks and statistical learningMathematical Physics and MathematicsThis book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing. Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include: • multilayer perceptron; • the Hopfield network; • associative memory models; • clustering models and algorithms; • t he radial basis function network; • recurrent neural networks; • nonnegative matrix factorization; • independent component analysis; •probabilistic and Bayesian networks; and • fuzzy sets and logic. Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning.Springeroai:cds.cern.ch:26913292019
spellingShingle Mathematical Physics and Mathematics
Du, Ke-Lin
Swamy, M N S
Neural networks and statistical learning
title Neural networks and statistical learning
title_full Neural networks and statistical learning
title_fullStr Neural networks and statistical learning
title_full_unstemmed Neural networks and statistical learning
title_short Neural networks and statistical learning
title_sort neural networks and statistical learning
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-1-4471-7452-3
http://cds.cern.ch/record/2691329
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