In a recent paper [2002 Phys. Rev. Lett. 88 174102], Bandt and Pompe propose permutation entropy （PE） as a natural complexity measure for arbitrary time series which may be stationary or nonstationary,deterministic ...In a recent paper [2002 Phys. Rev. Lett. 88 174102], Bandt and Pompe propose permutation entropy （PE） as a natural complexity measure for arbitrary time series which may be stationary or nonstationary,deterministic or stochastic.Their method is based on a comparison of neighbouring values.This paper further develops PE,and proposes the concept of fine-grained PE （FGPE） defined by the order pattern and magnitude of the difference between neighbouring values. This measure excludes the case where vectors with a distinct appearance are mistakenly mapped onto the same permutation type,and consequently FGPE becomes more sensitive to the dynamical change of time series than does PE,according to our simulation and experimental results.展开更多
Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method ...Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy features.Then,the fuzzy BLS takes the above entropy features as input to complete model training.Fuzzy BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational speed.Experimental results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.展开更多
心率变异性(hear trate variability,HRV)可以用于进行心脏相关疾病的预测、预防和预后评价等.结合心电散点图和符号动力学的方法,从ECG信号中提取HRV序列,绘制心电散点图,并对散点图中散点进行分区编号编码.计算不同编码的出现概率进...心率变异性(hear trate variability,HRV)可以用于进行心脏相关疾病的预测、预防和预后评价等.结合心电散点图和符号动力学的方法,从ECG信号中提取HRV序列,绘制心电散点图,并对散点图中散点进行分区编号编码.计算不同编码的出现概率进而计算整个序列信息熵.以该熵值作为心电特征用于识别和分类.实验得到窦性心律和房颤心律的分类正确率为86.67%,窦性心律与伴有失常心律的早搏分类正确率为90%.证明该方法能有效分类窦性心律与失常心律.展开更多
基金Project supported by the National High Technology Research and Development Program of China (Grant No 2007AA04Z238)the Qingdao Foundation for Development of Science and Technology,China (Grant No 06-2-2-10-JCH)
文摘In a recent paper [2002 Phys. Rev. Lett. 88 174102], Bandt and Pompe propose permutation entropy （PE） as a natural complexity measure for arbitrary time series which may be stationary or nonstationary,deterministic or stochastic.Their method is based on a comparison of neighbouring values.This paper further develops PE,and proposes the concept of fine-grained PE （FGPE） defined by the order pattern and magnitude of the difference between neighbouring values. This measure excludes the case where vectors with a distinct appearance are mistakenly mapped onto the same permutation type,and consequently FGPE becomes more sensitive to the dynamical change of time series than does PE,according to our simulation and experimental results.
基金supported in part by the Fundamental Research Funds for the Central Universities(Grant No.2021RC271)NSFC(Grants No.62120106011,52172323 and U22A2046).
文摘Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy features.Then,the fuzzy BLS takes the above entropy features as input to complete model training.Fuzzy BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational speed.Experimental results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.
文摘心率变异性(hear trate variability,HRV)可以用于进行心脏相关疾病的预测、预防和预后评价等.结合心电散点图和符号动力学的方法,从ECG信号中提取HRV序列,绘制心电散点图,并对散点图中散点进行分区编号编码.计算不同编码的出现概率进而计算整个序列信息熵.以该熵值作为心电特征用于识别和分类.实验得到窦性心律和房颤心律的分类正确率为86.67%,窦性心律与伴有失常心律的早搏分类正确率为90%.证明该方法能有效分类窦性心律与失常心律.
