互模糊熵中隶属函数的改进和影响分析  

Refining of the membership function in cross fuzzy entropy and its influence

作　　者：贺思艳[1] 李鹏[2] 刘澄玉[2] 吴学谦[2] 陈启军[3] 

机构地区：[1]山东电子职业技术学院自动化工程系,山东济南250200 [2]山东大学控制科学与工程学院,山东济南250061 [3]同济大学电子与信息工程学院,上海201804

出　　处：《山东大学学报（工学版）》2014年第1期63-68,共6页Journal of Shandong University（Engineering Science）

基　　金：山东省高等学校优秀教师国内访问学者经费资助项目;中国博士后科学基金面上资助项目(2013M530323);山东省优秀中青年科学家科研奖励基金资助项目(BS2012DX019)

摘　　要：为进一步提高互模糊熵(cross fuzzy entropy,X-FuzzyEn)算法的统计性能,引入了调整因子λ,定义了一类新的模糊隶属函数,提出了改进X-FuzzyEn算法。使用耦合噪声模型和耦合MIX(p)模型定量评价了改进算法的统计稳定性和相对一致性;通过实际心衰患者和健康志愿者之间的心动周期和舒张间期耦合分析,对改进算法的有效性进行了验证。结果表明,改进算法的统计性能显著提升,并可以有效区分心衰患者与健康志愿者。To further improve the statistical performances of cross fuzzy entropy （ X-FuzzyEn） algorithm, an adjustable factorλwas introduced and a refined X-FuzzyEn method was developed accordingly.Its statistical stability and relative consistency was tested by coupled noise and coupled MIX（ p） models.Then it was validated by the coupling analysis of heart rate and cardiac diastolic period series between heart failure patients and healthy subjects.Results indicated that the refined algorithm had significantly improved performances and it was capable to tell the differences between heart failure patients and healthy subjects.

关 键 词：生理信号变异性 互模糊熵 模糊隶属函数 心动周期 舒张间期 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]