摘要
周期信号的盲抽取在医学等领域具有重要的研究价值.对于此类信号的抽取需要利用先验知识对其周期进行较为准确的估计,多数算法对于目标信号周期估计误差十分敏感.文章针对此问题提出一种改进的周期特征信号盲抽取算法,首先通过先验知识估算最佳时延的存在区间并利用改进的时域相关函数对提取矩阵进行初始估计,再使用负熵作为目标函数并引入自相关函数确保抽取顺序,使用牛顿迭代法进行优化,达到最优结果.仿真和实际ECG数据测试表明,对比几种现行算法本文提出的算法抽取效果较好,并增强了周期估计误差的鲁棒性.
The research of extracting periodic signals is of great value in the field such as medicine. A precise estimation for period of target signals with priori knowledge is necessary in such kind of algorithms. But most of algorithms are sensitive to the error from the estimation. The algorithm proposed in the article including steps as follows： first roughly evaluate the extracting matrix with the improved time domain correlation function by evaluating the existing interval of optimizing time delay, use negentropy as the target function with the correlation function given into consideration to ensure the order and optimize it with Newton iterative method. The simulation and the experiment with real ECG data prove that the proposed algorithm can get a better result in the extraction than other algorithms, and show its robustness to the error of time delay.
出处
《计算机系统应用》
2014年第6期118-123,共6页
Computer Systems & Applications
关键词
盲抽取
时域相关函数
负熵
牛顿迭代法
BSE
time domain correlation function
negentropy
Newton iterative method
