改进非线性局部平均算法的混沌去噪研究  

Application of nonlinear local average algorithm in chaotic noise reduction

作　　者：席剑辉 韩敏 孙燕楠 

机构地区：[1]大连理工大学电子与信息工程学院

出　　处：《系统工程与电子技术》2005年第5期799-802,共4页Systems Engineering and Electronics

基　　金：国家自然科学基金资助课题(60374064)

摘　　要：基于混沌序列重构相空间理论,提出一种改进的局部平均非线性去噪方法。该方法在邻域选择、数据更新等方面进行了改进,更好地校正相空间中点的位置,使其逼近真实的混沌吸引子轨迹,重构吸引子结构,而且计算更为简单可靠。分别对Henon映射产生的混沌序列和实际观测的月太阳黑子混沌序列进行仿真研究。结果证明此方法能够高效地去除噪声,同时保留原非线性系统的混沌特性,并且很好地区分相空间中的邻近轨迹。Based on the chaotic theory of reconstructing phase space, an improved local average nonlinear noise reduction method is presented. This method is superior in some aspects such as selecting neighborhood and correcting points, and can better correct the position of data points in phase space to approximate the real chaotic attractor trajectories more closely. In this way, the attractor is reconstructed and the computational cost is reduced. Chaotic time series generated by Henon map and the observed monthly sunspot time series are respectively applied for noise reduction using this method. Simulation results show that the improved local average method can effectively reduce the noise, keep the chaotic characteristics of the nonlinear system and better distinguish the adjacent trajectories in the phase space.

关 键 词：局部平均 去噪 混沌信号 

分 类 号：TN91[电子电信—通信与信息系统]