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Neural Networks and Statistical Learning

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Cover of 'Neural Networks and Statistical Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Fundamentals of Machine Learning
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    Chapter 3 Perceptrons
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    Chapter 4 Multilayer Perceptrons: Architecture and Error Backpropagation
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    Chapter 5 Multilayer Perceptrons: Other Learning Techniques
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    Chapter 6 Hopfield Networks, Simulated Annealing, and Chaotic Neural Networks
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    Chapter 7 Associative Memory Networks
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    Chapter 8 Clustering I: Basic Clustering Models and Algorithms
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    Chapter 9 Clustering II: Topics in Clustering
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    Chapter 10 Radial Basis Function Networks
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    Chapter 11 Recurrent Neural Networks
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    Chapter 12 Principal Component Analysis
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    Chapter 13 Nonnegative Matrix Factorization
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    Chapter 14 Independent Component Analysis
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    Chapter 15 Discriminant Analysis
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    Chapter 16 Support Vector Machines
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    Chapter 17 Other Kernel Methods
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    Chapter 18 Reinforcement Learning
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    Chapter 19 Probabilistic and Bayesian Networks
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    Chapter 20 Combining Multiple Learners: Data Fusion and Emsemble Learning
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    Chapter 21 Introduction to Fuzzy Sets and Logic
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    Chapter 22 Neurofuzzy Systems
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    Chapter 23 Neural Circuits and Parallel Implementation
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    Chapter 24 Pattern Recognition for Biometrics and Bioinformatics
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    Chapter 25 Data Mining
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Citations

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Title
Neural Networks and Statistical Learning
Published by
Springer-Verlag London, January 2014
DOI 10.1007/978-1-4471-5571-3
ISBNs
978-1-4471-5570-6, 978-1-4471-5571-3
Authors

Du, Ke-Lin, Swamy, M. N. S., Ke-Lin Du, M. N. S. Swamy

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 746 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 <1%
United States 2 <1%
Canada 2 <1%
Germany 1 <1%
Brazil 1 <1%
Ecuador 1 <1%
Switzerland 1 <1%
Belgium 1 <1%
Netherlands 1 <1%
Other 2 <1%
Unknown 732 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 157 21%
Student > Ph. D. Student 124 17%
Student > Bachelor 101 14%
Researcher 59 8%
Student > Doctoral Student 42 6%
Other 93 12%
Unknown 170 23%
Readers by discipline Count As %
Computer Science 227 30%
Engineering 178 24%
Mathematics 29 4%
Physics and Astronomy 12 2%
Business, Management and Accounting 11 1%
Other 98 13%
Unknown 191 26%