机构地区: 吉林大学物理学院
出 处: 《吉林大学学报(工学版)》 2008年第4期950-954,共5页
摘 要: 改进了降低混沌中噪声的局部投影方法,建立了正交局部投影算法,根据混沌的确定性特征,提出了预测性邻点选取方法和参数选择法则。这种方法成功地应用于提取Henon混沌中的微弱信号,在信噪比不低于-80 dB的条件下,能够准确提取信号信息。数值实验表明,该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有效方法。 An orthogonal local projective algorithm was derived by improving local projective method on noise reduction in chaotic time series. According to the deterministic character of chaos, a predictive approach of neighborhood selection was presented and rules of parameter selection was proposed, which can extract weak signal in Henon c method has higher stability and reliability haos at SNR=-80 dB. Simulation results verified that the and is effective in weak signal extraction in chaos.