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Estimation in generalized uncertain-stochastic linear regressionстатья
- Автор: Borisov A.V.
- Сборник: [1992] Proceedings of the 31st IEEE Conference on Decision and Control
- Год издания: 1992
- Место издания: IEEE USA
- DOI: 10.1109/cdc.1992.371523
- Аннотация: The author considers the problem of optimally estimating a certain finite-dimensional vector, which is the result of a certain linear transformation of processes from a special class of stochastic and uncertain processes. Optimality of the estimate implies minimization of a minimax-stochastic criterion. A linear model of observations which contains random disturbances and has a discrete-continuous structure is assumed. The optimal estimate must be found as a linear operator of observations. Necessary and sufficient conditions for the linear estimate optimality are presented. The optimal filtering algorithm for uncertain-stochastic differential systems is obtained as an application of this estimation theory.
- Добавил в систему: Борисов Андрей Владимирович