Dictionary learning for VQ feature extraction in ECG beats classification
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- 作者：Tong Liua ; tongliu13@mails.jlu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Yujuan Si ; a ; c ; siyj@jlu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Dunwei Wenb ; dunweiw@athabascau.ca" class="auth_mail" title="E-mail the corresponding author ; Mujun Zanga ; d ; zangmj12@mails.jlu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Liuqi Langc ; langlqjlu@126.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：ECG beats ; Vector quantization ; Classification ; Feature extraction ; k-medoids ; k-means++
- 刊名：Expert Systems with Applications
- 出版年：2016
- 出版时间：1 July 2016
- 年：2016
- 卷：53
- 期：Complete
- 页码：129-137
- 全文大小：862 K
文摘
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We improve dictionary learning algorithm for vector quantization of ECG.
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The algorithm is employed to extract feature of ECG.
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The algorithm can avoid interference from dirty data.
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The algorithm is capable of increasing classification accuracy.
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An initial cluster centers selecting method is utilized to speed up the algorithm.