Dictionary learning for VQ feature extraction in ECG beats classification
作者：
Highlights：
• We improve dictionary learning algorithm for vector quantization of ECG.
• The algorithm is employed to extract feature of ECG.
• The algorithm can avoid interference from dirty data.
• The algorithm is capable of increasing classification accuracy.
• An initial cluster centers selecting method is utilized to speed up the algorithm.
摘要
•We improve dictionary learning algorithm for vector quantization of ECG.•The algorithm is employed to extract feature of ECG.•The algorithm can avoid interference from dirty data.•The algorithm is capable of increasing classification accuracy.•An initial cluster centers selecting method is utilized to speed up the algorithm.
论文关键词：ECG beats,Vector quantization,Classification,Feature extraction,k-medoids,k-means++
论文评审过程：Received 5 July 2015, Revised 1 January 2016, Accepted 2 January 2016, Available online 27 January 2016, Version of Record 13 February 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.01.031
