Classification of ECG waveforms by using RCE neural network and genetic algorithms

T. Ölmez

doi:10.1049/el:19971019

Classification of ECG waveforms by using RCE neural network and genetic algorithms

T. Ölmez^*

^*Corresponding author for this work

Department of Electronics and Communication Engineering

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

A modified restricted Coulomb energy (RCE) neural network is proposed for electrocardiogram (ECG) waveform classification. In the new algorithm, the locations of the centres of the hyperspheres are optimised in order to minimise the number of hyperspheres used and to improve classification performance. Optimisation is carried out with the genetic algorithm.

Original language	English
Pages (from-to)	1561-1562
Number of pages	2
Journal	Electronics Letters
Volume	33
Issue number	18
DOIs	https://doi.org/10.1049/el:19971019
Publication status	Published - 28 Aug 1997

Keywords

Genetic algorithms
Neural networks
Pattern recognition

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10.1049/el:19971019

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title = "Classification of ECG waveforms by using RCE neural network and genetic algorithms",

abstract = "A modified restricted Coulomb energy (RCE) neural network is proposed for electrocardiogram (ECG) waveform classification. In the new algorithm, the locations of the centres of the hyperspheres are optimised in order to minimise the number of hyperspheres used and to improve classification performance. Optimisation is carried out with the genetic algorithm.",

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AB - A modified restricted Coulomb energy (RCE) neural network is proposed for electrocardiogram (ECG) waveform classification. In the new algorithm, the locations of the centres of the hyperspheres are optimised in order to minimise the number of hyperspheres used and to improve classification performance. Optimisation is carried out with the genetic algorithm.

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KW - Pattern recognition

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JO - Electronics Letters

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Classification of ECG waveforms by using RCE neural network and genetic algorithms

Abstract

Keywords

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