文件名称:APEN
下载
别用迅雷、360浏览器下载。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
介绍说明－－下载内容均来自于网络，请自行研究使用
近似熵是一种衡量衡量非线性时间序列复杂性的非线性动力学分析方法，其物理意义
为熵值越大，时间序列的自我相似性越低，序
列越复杂，反之序列自我相似性越高；并且样
本熵对于序列长度依赖弱，仅需较短的数据就
能够得到稳健的熵值，同时其计算不需对数据
粗粒化，具有较好的抗干扰能力-Approximate entropy is a measure to measure the complex nonlinear dynamics of nonlinear time series analysis method, the physical meaning of entropy value is larger, the lower the self-similarity of the time series, the more complex the sequence, whereas sequence of self-similarity the higher and the sample entropy weak dependence for the length of the sequence, only shorter data can be healthy entropy value, calculated without data coarse-grained, with good anti-jamming capability
为熵值越大，时间序列的自我相似性越低，序
列越复杂，反之序列自我相似性越高；并且样
本熵对于序列长度依赖弱，仅需较短的数据就
能够得到稳健的熵值，同时其计算不需对数据
粗粒化，具有较好的抗干扰能力-Approximate entropy is a measure to measure the complex nonlinear dynamics of nonlinear time series analysis method, the physical meaning of entropy value is larger, the lower the self-similarity of the time series, the more complex the sequence, whereas sequence of self-similarity the higher and the sample entropy weak dependence for the length of the sequence, only shorter data can be healthy entropy value, calculated without data coarse-grained, with good anti-jamming capability
(系统自动生成,下载前可以参看下载内容)
下载文件列表
APEN.m