Similarity measures between vague sets and their application to electrocardiogram auto-recognition.
- Author:
Li TANG
1
;
Xiaoyun ZHANG
;
Xiao TANG
;
Zhiwen MO
Author Information
1. College of Mathematic and Computer Science, Mianyang Normal University, Mianyang 621000, China. tangli0929@163.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Electrocardiography;
methods;
Fuzzy Logic;
Humans;
Neural Networks (Computer);
Pattern Recognition, Automated;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2008;25(4):785-789
- CountryChina
- Language:Chinese
-
Abstract:
The similarity measures between Vague sets are one of the most important technologies in Vague sets, In this paper, the new similarity measures based on Huang Guoshun's related works are presented and applied in electrocardiogram auto-recognition. Based on medical requiresments, in this paper, the characteristic parameters of signals from Massachusettes Institute of Technology (database) have been picked up and studied with BP neural network. In the end, the electrocardiogram samples are classified with the use of those characteristic parameters. The result shows that the accuracy of recognition goes up to 99.04%.
