现代电子技术2017，Vol.40Issue(17)：40-43,4.DOI:10.16652/j.issn.1004-373x.2017.17.010
基于多尺度样本熵的时间序列复杂度研究
Time series complexity research based on multiscale sample entropy
摘要
Abstract
The multiscale sample entropy(MSE)is mostly used to analyze the time series complexity in 3D space. Since the time series complexity of MSE method can reduce the accuracy of the sample entropy estimation with the increase of time se-ries complexity,a multiscale sample entropy model is proposed. The experiments were carried out to verify the multiscale sam-ple entropy model. According to the different complexity of time sequences,the composite multiscale sample entropy (CMSE) and refined composite multiscale sample entropy(RCMSE)are used respectively to study and analyze the time series to obtain different simulation results. The result proves that the multi-scale sample entropy method can achieve the effect of improving the accuracy rate.关键词
时间序列/RCMSE/多尺度样本熵/复杂度分析Key words
time series/RCMSE/multiscale sample entropy/complexity analysis分类
信息技术与安全科学引用本文复制引用
尚传福..基于多尺度样本熵的时间序列复杂度研究[J].现代电子技术,2017,40(17):40-43,4.基金项目
重庆市统筹城乡教师教育研究中心工作室资助项目 （）
