An Recursive Total Least Mean P-Norm Algorithm Applied in Alpha-Stable Noise Environments

CHANG Dong-xia; FENG Da-zheng

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An Recursive Total Least Mean P-Norm Algorithm Applied in Alpha-Stable Noise Environments

更新时间：2025-07-16

- An Recursive Total Least Mean P-Norm Algorithm Applied in Alpha-Stable Noise Environments
- Acta Electronica Sinica Vol. 31, Issue 3, Pages: 426-428(2003)
- 作者机构：
  
  西安电子科技大学雷达信号处理重点实验室,陕西,西安,710071
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.3
- Published：2003
- 稿件说明：
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CHANG Dong-xia, FENG Da-zheng. An Recursive Total Least Mean P-Norm Algorithm Applied in Alpha-Stable Noise Environments[J]. Acta Electronica Sinica, 2003, 31(3): 426-428.
DOI：

CHANG Dong-xia, FENG Da-zheng. An Recursive Total Least Mean P-Norm Algorithm Applied in Alpha-Stable Noise Environments[J]. Acta Electronica Sinica, 2003, 31(3): 426-428. DOI：

摘要

本文给出了适应于α-稳定噪声环境的一种递归全局最小平均P-范数算法

其可用于递归计算自适应滤波和系统辨识问题的全局最小平均P-范数算法.针对α-稳定噪声的冲击性

本文所提出的自适应算法采用了有名的power迭代法

并通过计算机仿真比较了有关算法的性能.

Abstract

A recursive total least

-norm (RTLMP) algorithm is developed to recursively compute the total least

-norm solution for adaptive finite impulse response(FIR) filters.Due to the existence of the non-Gaussian

-stable noise

the performance of signal processing algorithms designed under the Gaussian assumption may degrade seriously.In this paper

a new adaptive algorithm based on the classical power iteration is developed which can minimize the

norm of the error function.The performance of the algorithm is evaluated via simulations.It is shown that the new algorithm achieves superior convergence rate.

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