Optimal non-linear estimation for distributed-parameter systems via the partition theorem
作者:
KEIGO WATANABE,
TOSHIO YOSHIMURA,
TAKASHI SOEDA,
期刊:
International Journal of Systems Science
(Taylor Available online 1980)
卷期:
Volume 11,
issue 9
页码: 1113-1130
ISSN:0020-7721
年代: 1980
DOI:10.1080/00207728008967078
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
This paper considers the estimation problem for non-linear distributed-parameter systems via the ‘Partition Theorem’. First, the aposterioriprobability for the state is derived for the estimation of non-linear distributed-parameter systems. Secondly, linear systems excited by a white gaussian noise and with non-gaussian initial state are considered as a special class of the problem. Thea posterioriprobability for the state, the optimal estimates and corresponding error covariance matrices are obtained by using the properties of the fundamental solution for the differential operator. Finally, it is shown that on approximate expression for the solution of the problem is also derived by applying a gaussian sum approximation technique.
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