The Conditionally Minimax Nonlinear Filtering Method and Modern Approaches to State Estimation in Nonlinear Stochastic Systems
- Autores: Borisov A.V.1, Bosov A.V.1, Kibzun A.I.2, Miller G.B.1, Semenikhin K.V.2
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Afiliações:
- Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
- Moscow Aviation Institute
- Edição: Volume 79, Nº 1 (2018)
- Páginas: 1-11
- Seção: 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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Resumo
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.
Sobre autores
A. Borisov
Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Autor responsável pela correspondência
Email: aborisov@frccsc.ru
Rússia, Moscow
A. Bosov
Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: aborisov@frccsc.ru
Rússia, Moscow
A. Kibzun
Moscow Aviation Institute
Email: aborisov@frccsc.ru
Rússia, Moscow
G. Miller
Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: aborisov@frccsc.ru
Rússia, Moscow
K. Semenikhin
Moscow Aviation Institute
Email: aborisov@frccsc.ru
Rússia, Moscow
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