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ECG Signal Processing, Classification and Interpretation

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Cover of 'ECG Signal Processing, Classification and Interpretation'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to ECG Interpretation
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    Chapter 2 An Introduction to ECG Signal Processing and Analysis
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    Chapter 3 ECG Signal Analysis, Classification, and Interpretation: A Framework of Computational Intelligence
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    Chapter 4 A Generic and Patient-Specific Electrocardiogram Signal Classification System
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    Chapter 5 Model-Based Atrial Fibrillation Detection
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    Chapter 6 An Introduction to the Use of Evolutionary Computation Techniques for Dealing with ECG Signals
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    Chapter 7 Electrocardiogram Application Based on Heart Rate Variability Ontology and Fuzzy Markup Language
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    Chapter 8 Learning in Artificial Neural Networks
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    Chapter 9 A Review of Kernel Methods in ECG Signal Classification
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    Chapter 10 Hyperellipsoidal Classifier for Beat Classification in ECG Signals
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    Chapter 11 Evolutionary Optimization of ECG Feature Extraction Methods: Applications to the Monitoring of Adult Myocardial Ischemia and Neonatal Apnea Bradycardia Events
Attention for Chapter 10: Hyperellipsoidal Classifier for Beat Classification in ECG Signals
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Citations

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Chapter title
Hyperellipsoidal Classifier for Beat Classification in ECG Signals
Chapter number 10
Book title
ECG Signal Processing, Classification and Interpretation
Published by
Springer, London, January 2012
DOI 10.1007/978-0-85729-868-3_10
Book ISBNs
978-0-85729-867-6, 978-0-85729-868-3
Authors

G. Bortolan, I. Christov, W. Pedrycz

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 33%
Researcher 1 33%
Student > Master 1 33%
Readers by discipline Count As %
Engineering 2 67%
Medicine and Dentistry 1 33%

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