【作者】 李辉；

【Author】 LI Hui (Electronic Engineering and Information Science Department,USTC,Hefei,Anhui,230027,China)

【机构】 中国科学技术大学电子工程与信息科学系；

【摘要】 针对中低信噪比下含噪混沌信号的噪声抑制问题,提出了一种蒙特卡罗局部抽样、全局迭代估计的混沌信号消噪新算法。该算法根据混沌映射建立混沌信号消噪问题的最大后验估计模型,首先对每一个样点利用局部蒙特卡洛方法得出该点的局部最优估计,然后对整段信号进行多次迭代,最终得到全局的最优估计。相对于Farmer算法、粒子滤波算法和基于卡尔曼滤波的算法,本文提出的算法具有实现简单,并行度高的特点。仿真实验表明该算法能有效地去除混沌信号中混入的加性噪声,能够获得很高的信噪比增益。更多还原

【Abstract】 In this paper a new noise reduction algorithm for chaos signal based on localized Monte Carlo sampling and global iterative estimation is presented.The maximum a posteriori estimation model is constructed according to the chaotic map firstly.Then the local optimum estimate is obtained through the localized Monte Carlo sampling method.The global optimum estimate can be achieved through the several iterative processing on the whole signal segment.The algorithm proposed in this paper can be implemented simply and parallel.The simulations show that the algorithm can eliminate the additive noise involved in the chaotic signal effectively and the Signal Noise Ratio(SNR) of processed signal can be improved remarkably.更多还原