基于滑动窗与韧性函数的递归最小p范数滤波方法
doi: 10.3724/SP.J.1146.2005.00468
Adaptive Generalized Recursive Least p-Norm Filtering Algorithm Based on Minimum Dispersion Criterion
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摘要: 稳定分布可以更好地描述实际应用中所遇到的具有显著脉冲特性的随机信号和噪声。与其它统计模型不同， 稳定分布没有统一闭式的概率密度函数，其二阶及二阶以上统计量均不存在。针对系统中存在独立SS噪声与高斯噪声，该文基于SSG分布模型，提出了一种混合噪声环境下基于滑动窗与韧性函数自适应广义递归最小p范数滤波算法，并对算法进行了分析。计算机模拟和分析表明，这种算法是一种在SSG分布背景噪声条件下具有良好鲁棒性的方法。Abstract: Alpha stable distribution, a generalization of Gaussian, is better for modeling impulsive noises than Gaussian distribution in signal processing. This class of process has no close form of probability density function and finite second order moments. In this paper, a new adaptive generalized recursive least p-norm filtering algorithm is proposed based on SSG noise model. The simulation experiments show that the proposed new algorithm is more robust than the conventional algorithm.
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