A new algorithm for state estimation of stochastic linear discretesystems

Ahmed M.S.

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A new algorithm for state estimation of stochastic linear discretesystems

机译：随机线性离散系统状态估计的新算法

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摘要

A novel algorithm is proposed for state estimation of linear discrete-time systems. The procedure performs explicit minimization of the innovation variance and is based upon the principle of pseudo linear regression (PLR) method. Sufficient conditions for algorithm convergence are also derived

机译：提出了一种新的线性离散时间系统状态估计算法。该程序根据伪线性回归（PLR）方法的原理对创新方差进行显式最小化。还导出了算法收敛的充分条件

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《IEEE Transactions on Automatic Control》 |1994年第8期|p.1652-1656|共5页
作者
Ahmed M.S.;
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正文语种 eng
中图分类自动化系统;
关键词
discrete time systems; estimation theory; filtering and prediction theory; minimisation; state estimation; statistical analysis; stochastic systems; algorithm convergence; innovation variance minimization; linear discrete-time systems; pseudo linear regression; sta;

机译：离散时间系统;估计理论;过滤和预测理论;最小化;状态估计;统计分析;随机系统;算法收敛;创新方差最小化;线性离散时间系统;伪线性回归;sta;

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A new algorithm for state estimation of stochastic linear discretesystems

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