Filtering problem (stochastic processes)
In the theory of stochastic processes, the filtering problem is a mathematical model for a number of state estimation problems in signal processing and related fields. The general idea is to establish a "best estimate" for the true value of some system from an incomplete, potentially noisy set of observations on that system. The problem of optimal non-linear filtering (even for the non-stationary case) was solved by Ruslan L. Stratonovich (1959, 1960), see also Harold J. Kushner's work and Moshe Zakai's, who introduced a simplified dynamics for the unnormalized conditional law of the filter known as Zakai equation. The solution, however, is infinite-dimensional in the general case. Certain approximations and special cases are well understood: for example, the linear filters are optimal fo
Filtering problem (stochastic processes)Catalog of articles in probability theoryDamiano BrigoFilterFiltering problemFiltering theoryInnovation (signal processing)Jan H. van SchuppenKalman filterKushner equationList of statistics articlesMaamar BettayebMoshe ZakaiMoving horizon estimationNonlinear filterParticle filterRobert LiptserSanjoy K. MitterSmoothing problem (stochastic processes)Switching Kalman filterZakai equation
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Filtering problem (stochastic processes)
In the theory of stochastic processes, the filtering problem is a mathematical model for a number of state estimation problems in signal processing and related fields. The general idea is to establish a "best estimate" for the true value of some system from an incomplete, potentially noisy set of observations on that system. The problem of optimal non-linear filtering (even for the non-stationary case) was solved by Ruslan L. Stratonovich (1959, 1960), see also Harold J. Kushner's work and Moshe Zakai's, who introduced a simplified dynamics for the unnormalized conditional law of the filter known as Zakai equation. The solution, however, is infinite-dimensional in the general case. Certain approximations and special cases are well understood: for example, the linear filters are optimal fo
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In the theory of stochastic pr ...... atic-Gaussian control problem.
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在随机过程理論中的濾波問題(Filtering proble ...... 如在LQG控制最佳控制問題中,其估測部份的解就是卡爾曼濾波。
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Filtering problem (stochastic processes)
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濾波問題
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In the theory of stochastic pr ...... linear filters are optimal fo
@en
在随机过程理論中的濾波問題(Filtering proble ...... 如在LQG控制最佳控制問題中,其估測部份的解就是卡爾曼濾波。
@zh