The Conditionally Minimax Nonlinear Filtering Method and Modern Approaches to State Estimation in Nonlinear Stochastic Systems
- 作者: Borisov A.V.1, Bosov A.V.1, Kibzun A.I.2, Miller G.B.1, Semenikhin K.V.2
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隶属关系:
- Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
- Moscow Aviation Institute
- 期: 卷 79, 编号 1 (2018)
- 页面: 1-11
- 栏目: Topical Issue
- URL: https://ogarev-online.ru/0005-1179/article/view/150746
- DOI: https://doi.org/10.1134/S0005117918010010
- ID: 150746
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详细
We consider, in chronological order, the main results that have defined the concept of conditionally minimax nonlinear filtering. This would let us to follow all the evolution stages of this universal method, from a particular application, through basic mathematical concepts, to an advanced theory able to solve a wide class of robust estimation problems in linear and nonlinear stochastic systems.
作者简介
A. Borisov
Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
编辑信件的主要联系方式.
Email: aborisov@frccsc.ru
俄罗斯联邦, Moscow
A. Bosov
Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: aborisov@frccsc.ru
俄罗斯联邦, Moscow
A. Kibzun
Moscow Aviation Institute
Email: aborisov@frccsc.ru
俄罗斯联邦, Moscow
G. Miller
Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: aborisov@frccsc.ru
俄罗斯联邦, Moscow
K. Semenikhin
Moscow Aviation Institute
Email: aborisov@frccsc.ru
俄罗斯联邦, Moscow
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