计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (34): 130-133.DOI: 10.3778/j.issn.1002-8331.2009.34.040

• 数据库、信号与信息处理 • 上一篇    下一篇

稳定分布噪声下非线性PAR系统辨识新方法

查代奉1,江金龙1,姜玉林1,邱天爽1,2   

  1. 1.九江大学 电子工程学院,江西 九江 332005
    2.大连理工大学 电子与信息工程学院,辽宁 大连 116024
  • 收稿日期:2008-01-09 修回日期:2009-07-29 出版日期:2009-12-01 发布日期:2009-12-01
  • 通讯作者: 查代奉

Identification of nonlinear PAR system based on non-Gaussian stable noise

ZHA Dai-feng1,JIANG Jin-long1,JIANG Yu-lin1,QIU Tian-shuang1,2   

  1. 1.College of Electronic Engineering,Jiujiang University,Jiujiang,Jiangxi 332005,China
    2.School of Electronic and Information Engineering,Dalian University of Technology,Dalian,Liaoning 116024,China
  • Received:2008-01-09 Revised:2009-07-29 Online:2009-12-01 Published:2009-12-01
  • Contact: ZHA Dai-feng

摘要: 描述了稳定分布的谱表示,提出了共变谱密度的概念,得到一种基于自共变序列与共变谱的稳定分布白噪声与有色噪声的概念及其判断标准,对传统意义上的白噪声进行了广义化,依据多项式自回归(PAR)系统模型,对基于稳定白噪声输入的系统输出非线性稳定有色噪声建立其非线性PAR模型,提出基于最小P范数的EIRLP算法对非线性PAR系统进行辨识。模拟和分析表明,这种算法是一种在高斯和分数低阶 稳定分布噪声条件下具有良好韧性的非线性系统辨识方法,是对传统的二阶统计量基础上的系统辨识方法的改造与推广。

关键词: α-稳定分布, 共变谱, 非线性系统, 最小P范数

Abstract: Stable processes can better model the impulsive random signals and noises in physical observation.This paper briefly describes its spectral representation,proposes a new different spectral density from power spectrum density of second order processes,thus can get a new concept of stable white noise based on covariation spectrum,and a method of identification of nonlinear PAR system based on least p-norm.Simulation and analysis show that the method is robust and generalizes the conventional method based on second order statistics.

Key words: alpha stable distribution, ovariation spectrum, nonlinear system, least p-norm

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