计算机工程

• 人工智能及识别技术 • 上一篇    下一篇

基于GA的心电信号稀疏分解MP算法改进

吴怡之a,刘文轩a,b   

  1. (东华大学 a. 信息科学与技术学院;b. 数字化纺织服装技术教育部工程研究中心,上海 201620)
  • 收稿日期:2012-09-03 出版日期:2013-09-15 发布日期:2013-09-13
  • 作者简介:吴怡之(1969-),女,副教授、博士,主研方向:智能控制,遗传算法;刘文轩,硕士研究生
  • 基金项目:

    国家自然科学基金资助项目(71171045/G0104)

Improvement of Electrocardio Signal Sparse Decomposition MP Algorithm Based on GA

WU Yi-zhi a, LIU Wen-xuan a,b   

  1. (a. College of Information Sciences and Technology; b. Engineering Research Center of Digitized Textile & Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China)
  • Received:2012-09-03 Online:2013-09-15 Published:2013-09-13

摘要:

基于遗传算法(GA)的信号稀疏分解算法运算量较大。为解决该问题,提出一种基于GA的心电信号匹配追踪改进算法。结合心电信号的特征,根据信号特征波形建立窗函数,将信号分为能量集中和稀疏部分,分别采用不同的算法流程和参数。实验结果表明,该改进算法的运算量较原算法降低了1/3,能提高心电信号稀疏分解的运算速度和压缩处理性能。

关键词: 心电信号, 遗传算法, 匹配追踪算法, 信号压缩, 稀疏分解, 压缩比

Abstract:

Aiming at the higher computing complexity based on Genetic Algorithm(GA) signal sparse decomposition algorithm, the electrocardio signal Matching Pursuit(MP) improved algorithm based on GA is proposed. It is combined the characteristics of electrocardio signal, and the window functions are established by electrocardio signal characteristic waveform. The signal is divided into energy concentrated and sparse parts, and is respectively processed using a different algorithm procedure and parameters. Experimental results show that the amount of computation is reduced by 1/3 than the original algorithm, this algorithm improves the computing speed of the electrocardio signal sparse decomposition and compression processing performance.

Key words: electrocardio signal, Genetic Algorithm(GA), Matching Pursuit(MP) algorithm, signal compression, sparse decomposition, compression ratio

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