作　　者： ; ; ;

机构地区： 吉林大学物理学院

出　　处： 《物理学报》 2010年第5期3049-3056,共8页

摘　　要： 根据混沌的确定性和几何结构特征,提出了预测性邻点选取方法和基于Delaunay三角化的邻点选取方法,改进了降低混沌中噪声的投影方法,建立了新的正交局部投影算法,给出了优化参数选择法则.这种方法成功地应用于提取Lorenz混沌中的微弱信号,在信噪比不低于-80dB条件下,能够准确提取信号信息.数值实验表明该投影滤波方法具有高度的稳定性和可靠性,是提取混沌中微弱信号的十分有效方法. According to deterministic character and geometric property of chaotic system,the predictive method of neighborhood selection and the approach of neighborhood selection based on Delaunay triangulation were presented,and a new orthogonal local projective algorithm was derived by improvement of local projective method for noise reduction in chaotic time series,and rules of selection of optimal parameters were suggested. The method was successfully applied to extract weak signals in Lorenz chaos,that provided signal to noise ratio not lower than-80 dB. Computer simulation shows that this projective filtering method has great stability and reliability,and is effective for extracting weak signals in chaos.

关 键 词： 信号提取 正交局部投影 混沌 参数优化

领　　域： [自动化与计算机技术] [自动化与计算机技术]