Human Identification System Research with the Electrocardiograms Based on the Neural Network

Jia Lun Lin

doi:10.4028/www.scientific.net/AMR.926-930.1104

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 926-930Human Identification System Research with the...

Human Identification System Research with the Electrocardiograms Based on the Neural Network

Abstract:

Based on existing researches at home and abroad, an intensive study of ECG signal preprocessing, feature extraction, feature analysis and feature weight analysis was made in the Paper neural network classifier was designed to realize the ECG identification and it was optimized by GA algorithm and DNA algorithm. The main research was concluded as follows. Firstly, extracting the preprocessing and feature of ECG signal. We have analyzed the frequency of ECG signal and the noise signal included by using wavelet and wavelet threshold methods filter the low and high frequency noise in ECG signal. Secondly, analyzing weight of ECG feature and selecting the optimal feature subset. Evaluated by the accuracy rate of BP neural network classification, the optimal characteristics for identification subset is determined then. Thirdly, designing and optimizing the neural network classifier. As the BP neural network has the Problems of easily falling into local minimum and being not convergence, GA and DNA algorithm are used to optimize it.

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Periodical:

Advanced Materials Research (Volumes 926-930)

Pages:

1104-1107

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.926-930.1104

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Online since:

May 2014

Authors:

Jia Lun Lin*

Keywords:

DNA Algorithm, Electrocardiogram (ECG), GA Algorithm, Human Identification, Neural Network (NN), Wavelet Transform (WT)

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