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。
Aiming at the higher computing complexity based on electrocardio signal Matching Pursuit（MP） improved algorithm based Genetic Algorithm（GA） signal sparse decomposition algorithm, the 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.
出处
《计算机工程》
CAS
CSCD
2013年第9期250-253,共4页
Computer Engineering
基金
国家自然科学基金资助项目(71171045/G0104)
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
electrocardio signal
Genetic Algorithm（GA）
Matching Pursuit（MP） algorithm
signal compression
sparse decomposition
compression ratio
