Neural Networks and Statistical Learning (Record no. 58981)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04096nam a22005055i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-1-4471-5571-3 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200421112553.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 131206s2014 xxk| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781447155713 |
| -- | 978-1-4471-5571-3 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 100 1# - AUTHOR NAME | |
| Author | Du, Ke-Lin. |
| 245 10 - TITLE STATEMENT | |
| Title | Neural Networks and Statistical Learning |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XXVII, 824 p. 166 illus., 68 illus. in color. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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 chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Swamy, M. N. S. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-1-4471-5571-3 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | London : |
| -- | Springer London : |
| -- | Imprint: Springer, |
| -- | 2014. |
| 336 ## - | |
| -- | text |
| -- | txt |
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| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Pattern recognition. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Neural networks (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Mathematical Models of Cognitive Processes and Neural Networks. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Pattern Recognition. |
| 912 ## - | |
| -- | ZDB-2-ENG |
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