Approximate maximum likelihood parameter estimates for stochastic distributed parameter systems

被引：0
|
作者：
Leland, R
机构：
来源：
PROCEEDINGS OF THE 1997 AMERICAN CONTROL CONFERENCE, VOLS 1-6 | 1997年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We describe a fast method to calculate maximum likelihood parameter estimates for stochastic distributed parameter systems from sampled data. We characterize the observations by an approximate one step predictor that uses a fixed number of past observations, and its error covariance. From these we calculate the log-likelihood functional, and find the estimate by iterative search. Estimators for an integral equation and two heat equations driven by white noise are derived and simulated.
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页码：3693 / 3697
页数：5
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