A NEW PREDICTION ALGORITHM USING COVARIANCE INFORMATION IN LINEAR CONTINUOUS SYSTEMS

被引：5
|
作者：
NAKAMORI, S
机构：
[1] Department of Technology, Faculty of Education, Kagoshima University, Kagoshima, 890
来源：
AUTOMATICA | 1991年 / 27卷 / 06期
关键词：
PREDICTION; STOCHASTIC PROCESS; LINEAR CONTINUOUS SYSTEM; WIENER-HOPF INTEGRAL EQUATION;
D O I：
10.1016/0005-1098(91)90143-P
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a new type of predictor, which uses the covariance information of the signal and the observation noise, for white Gaussian plus colored observation noise in linear continuous stochastic systems. This method has the advantage that one need not assume that the state-space model is known as prior necessary information. A numerical simulation example shows that the presented prediction algorithm is feasible.
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页码：1055 / 1058
页数：4
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