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Condition Monitoring Using Computational Intelligence Methods

Overview of attention for book
Cover of 'Condition Monitoring Using Computational Intelligence Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Condition Monitoring in Mechanical and Electrical Systems
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    Chapter 2 Data Processing Techniques for Condition Monitoring
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    Chapter 3 Multi-Layer Perceptron for Condition Monitoring in a Mechanical System
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    Chapter 4 Bayesian Approaches to Condition Monitoring
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    Chapter 5 The Committee of Networks Approach to Condition Monitoring
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    Chapter 6 Gaussian Mixture Models and Hidden Markov Models for Condition Monitoring
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    Chapter 7 Fuzzy Systems for Condition Monitoring
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    Chapter 8 Rough Sets for Condition Monitoring
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    Chapter 9 Condition Monitoring with Incomplete Information
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    Chapter 10 Condition Monitoring Using Support Vector Machines and Extension Neural Networks Classifiers
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    Chapter 11 On-line Condition Monitoring Using Ensemble Learning
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    Chapter 12 Conclusion
Attention for Chapter 6: Gaussian Mixture Models and Hidden Markov Models for Condition Monitoring
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Citations

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Chapter title
Gaussian Mixture Models and Hidden Markov Models for Condition Monitoring
Chapter number 6
Book title
Condition Monitoring Using Computational Intelligence Methods
Published by
Springer, London, January 2012
DOI 10.1007/978-1-4471-2380-4_6
Book ISBNs
978-1-4471-2379-8, 978-1-4471-2380-4
Authors

Tshilidzi Marwala, Marwala, Tshilidzi

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 1 100%
Readers by discipline Count As %
Mathematics 1 100%

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