【摘要】 基于局部相关原理,提出了一种可以有效实现混沌信号和噪声分离的方法。通过分析混沌信号在一定维数的相空间中存在的局部相关性,阐明了混沌信号内在的局部特征,引入循环相关算法对相空间中的相点进行有限次相关迭代以重新估计各个相点的值,利用相空间重构技术从这些新的相点中恢复出原始信号序列。试验仿真结果表明,该方法具有良好的噪声抑制能力和计算收敛性,算法简洁等优点。滤波效果与背景噪声类型无关。更多还原

【Abstract】 Based on the local correlation principle, a practical method was put forth to separate chaotic signal from noise background. The intrinsic correlation characteristics of chaotic signal is obtained by analyzing the Hesse matrix of chaotic signal, then the round correlation algorithm is introduced to adjust each primary dot in embedded phase space. At last, the original sequence can be drawn out from the observed signal sequence by disembedology collisions. The results of experiments show that it is a effective way to reduce noise and has a strongly computation convergence. It also has some superior performances such as independent of noise style, concise compute process, etc.更多还原