Supervised Learning Methods for ECG Classification/ Neural Networks and SVM Approaches - Chapter 12
Stanislaw Osowski, Linh Tran Hoai, and Tomasz Markiewicz
This page provides supplementary information and relevant links for Chapter 12 in Advanced Methods for ECG Analysis, which is co-edited by Francisco Azuaje and Patrick McSharry, and is published by Artech House. The main URL for this book can be found here, together with ordering information. Much of the software associated with this book can be found here.
Links:
- ECGtools - A selection of ECG analysis tools in Matlab including a self-explaining QRS detector, filtering tools and HRV analysis algorithms. Includes FIR, SVD, ICA and Wiener filtering code.
- Netlab -- A free set of pattern recognition & neural network tools in Matlab by Ian Nabney. the associated book is simply wonderful.
Contents:
12.1 Introduction
12.2 Generation of Features
12.2.1 Hermite Basis Function Expansion
12.2.2 HOS Features of the ECG
12.3 Supervised Neural Classifiers
12.3.1 Multilayer Perceptron
12.3.2 Hybrid Fuzzy Network
12.3.3 TSK Neuro-Fuzzy Network
12.3.4 Support Vector Machine Classifiers
12.4 Integration of Multiple Classifiers
12.5 Results of Numerical Experiments
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12.6 Conclusions