摘要
变尺度概率净化法是一种混沌时间序列非线性动力学降噪方法,该方法需对整个相空间点列做联合处理,因此算法的计算量和所需内存量会随着每个轨道点的修正参考点数和嵌入维数的增加而呈指数增长.根据变尺度概率净化法的特点,对前向概率和转移概率的估计方法作了一些改进,使算法的运算量减小到了原来的0·27左右,而降噪性能并没有下降,并提出了数据较长情况下的算法实现结构,大大降低了算法运行所需内存.
The scaled probabilistic cleaning method is one of nonlinear noise reduction methods for chaotic time series, whose calculation quantity and needed memory volume increase exponentially with the number of reference points and the embedding dimension because of the joint processing of all data points in phase space. An optimized method, which modifies the estimation of forward probabilities and transition probabilities is proposed, and the computing workload is reduced to about 0.27 times that of the original method without degradation in noise reduction performance. The implementation of the method for the long time series also reduces the needed memory size.
出处
《物理学报》
SCIE
EI
CAS
CSCD
北大核心
2005年第10期4596-4601,共6页
Acta Physica Sinica
基金
国家安全重大基础研究项目(批准号:5132102ZZT32)
国家重点实验室基金(批准号:514450801JB1101)资助的课题.~~
