Neural Networks and Statistical Learning

Ke-Lin Du () and M. N. S. Swamy ()
Additional contact information
Ke-Lin Du: Concordia University, Department of Electrical and Computer Engineering
M. N. S. Swamy: Concordia University, Department of Electrical and Computer Engineering

in Springer Books from Springer

Date: 2019
Edition: 2nd ed. 2019
ISBN: 978-1-4471-7452-3
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Chapters in this book:

Ch Chapter 1 Introduction

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

Ch Chapter 10 Clustering II: Topics in Clustering

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

Ch Chapter 11 Radial Basis Function Networks

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

Ch Chapter 12 Recurrent Neural Networks

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

Ch Chapter 13 Principal Component Analysis

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

Ch Chapter 14 Nonnegative Matrix Factorization

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

Ch Chapter 15 Independent Component Analysis

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

Ch Chapter 16 Discriminant Analysis

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

Ch Chapter 17 Reinforcement Learning

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

Ch Chapter 18 Compressed Sensing and Dictionary Learning

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

Ch Chapter 19 Matrix Completion

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

Ch Chapter 2 Fundamentals of Machine Learning

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

Ch Chapter 20 Kernel Methods

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

Ch Chapter 21 Support Vector Machines

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

Ch Chapter 22 Probabilistic and Bayesian Networks

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

Ch Chapter 23 Boltzmann Machines

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

Ch Chapter 24 Deep Learning

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

Ch Chapter 25 Combining Multiple Learners: Data Fusion and Ensemble Learning

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

Ch Chapter 26 Introduction to Fuzzy Sets and Logic

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

Ch Chapter 27 Neurofuzzy Systems

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

Ch Chapter 28 Neural Network Circuits and Parallel Implementations

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

Ch Chapter 29 Pattern Recognition for Biometrics and Bioinformatics

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

Ch Chapter 3 Elements of Computational Learning Theory

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

Ch Chapter 30 Data Mining

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

Ch Chapter 31 Big Data, Cloud Computing, and Internet of Things

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

Ch Chapter 4 Perceptrons

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

Ch Chapter 5 Multilayer Perceptrons: Architecture and Error Backpropagation

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

Ch Chapter 6 Multilayer Perceptrons: Other Learing Techniques

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

Ch Chapter 7 Hopfield Networks, Simulated Annealing, and Chaotic Neural Networks

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

Ch Chapter 8 Associative Memory Networks

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

Ch Chapter 9 Clustering I: Basic Clustering Models and Algorithms

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

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprbok:978-1-4471-7452-3

Ordering information: This item can be ordered from
http://www.springer.com/9781447174523

DOI: 10.1007/978-1-4471-7452-3

Access Statistics for this book

More books in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().