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Wiener状态去卷滤波器
引用本文:邓自立,孙书利,郭金柱.Wiener状态去卷滤波器[J].控制理论与应用,2001,18(4):508-512.
作者姓名:邓自立  孙书利  郭金柱
作者单位:黑龙江大学应用数学研究所黑龙江大学自动化系,
基金项目:国家自然科学基金 ( 6 97740 19)资助项目
摘    要:应用现代时间序列分析方法,基于ARMA新息模型提出了一类带多重观测滞后和带滑动平均(MA)有色观测噪声系统的Wiener状态去卷滤波器,它具有渐近稳定性和ARMA递推形式,可统一处理滤波、平滑和预报问题,且可用于解决带ARMA有色观测噪声系统状态估计和信号Wiener滤波与反卷积问题,二个仿真例子说明了其有效性。

关 键 词:状态估计  反卷积  信号处理  Wiener滤波器  时域方法  传递函数
文章编号:1000-8152(2001)04-0508-05
收稿时间:1998/12/21 0:00:00
修稿时间:1998年12月21

Wiener State Deconvolution Filters
DENG Zi-li,SUN Shu-li and GUO Jin-zhu.Wiener State Deconvolution Filters[J].Control Theory & Applications,2001,18(4):508-512.
Authors:DENG Zi-li  SUN Shu-li and GUO Jin-zhu
Affiliation:Institute of Applied Mathematics, Department of Automation, Heilongjiang University, Harbin,150080,P.R.China;Institute of Applied Mathematics, Department of Automation, Heilongjiang University, Harbin,150080,P.R.China;Institute of Applied Mathematics, Department of Automation, Heilongjiang University, Harbin,150080,P.R.China
Abstract:Using the modern time series analysis method, based on ARMA innovation model, the Wiener state deconvolution filters are presented for a class of systems with multiple measurement delays and with moving average(MA) coloured measurement noises. They have the asymptotic stability and autoregressive moving average (ARMA) recursive form. They can handle filtering, smoothing and prediction problems in a unified framework, and can be applied to solve the state estimation problem for systems with ARMA coloured measurement noise, and signal Wiener filtering and deconvolution problems. Two simulation examples show their effectiveness.
Keywords:state estimation  signal processing  deconvolution  Wiener filter  time  domain approach  modern time series analysis method
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