Journal Article10.1016/0020-0255(70)90035-6
Nonlinear sequential algorithms for estimation under uncertainty
M. Z. Dajani,Andrew P. Sage +1 more
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TL;DR: This paper derives nonlinear sequential filter algorithms for conditional mean estimation of a Gauss Markov process when there is uncertainty as to the presence of the GaussMarkov process (signal process) in the observation.
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About: This article is published in Information Sciences. The article was published on 01 Oct 1970. The article focuses on the topics: Kalman filter & Filter (signal processing).
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Citations
State estimation for continuous-time system with interrupted observation
Yoshikazu Sawaragi,Tohru Katayama,S. Fujishige +2 more
- 01 Dec 1973
TL;DR: In this article, the minimum variance estimator for linear continuous-time systems with the interrupted observation mechanism is derived, which is characterized in terms of the jump Markov process taking on the values of 0 or 1.
22
1971 kyow symposium paper: Optimal stochastic control for discrete-time linear system with interrupted observations
Shohei Fujita,Takeshi Fukao +1 more
TL;DR: In this article, an optimal control policy for a discrete-time linear system with interrupted observations and an expected quadratic cost is proposed, which is realized by cascading a nonlinear estimator, which computes the conditional mean of the state vector, with the optimal feedback gain matrix in which all uncertainties are removed.
15
Adaptive estimation and stochastic control for uncertain models
A. Y. Lee,C. S. Sims +1 more
TL;DR: In this paper, the problem of estimation-under-uncertainty is formulated using the assumption that the model is one of a set of finite number of candidate models, and recursive estimation and identification algorithms are presented.
Brief paper: Finite-state, discrete-time optimization with randomly varying observation quality
TL;DR: A generalized, finite-state version of the linear-quadratic-Gaussian control problem with interrupted observations is formed and upper and lower bounds on optimal cost are determined for the case where the mechanism that varies observation quality is completely observed.
4
Optimal estimation for continous system with jump process
S. Fujishige,Y. Sawaragi +1 more
TL;DR: In this article, the minimum variance estimator for a class of linear continuous systems modulated by a multivalued jump Markov process is derived for the case of continuous systems.
4
References
•Book
Estimation theory with applications to communications and control
Andrew P. Sage,James L. Melsa,W. J. Steinway +2 more
- 01 Jan 1979
TL;DR: This text provides a comprehensive treatment of estimation theory which should be suitable for graduate level engineers and is suitable for students studying estimation theory.
820
•Book
Optimum systems control
A. P. Sage,C. C. White,George M. Siouris +2 more
- 01 Jan 1968
TL;DR: Optimum systems control, Optimum system control, maximization systems control as discussed by the authors, maximization system control (OPC), maximisation systems control (MSC), optimum systems control
725
Optimal recursive estimation with uncertain observation
TL;DR: Minimum mean-square estimators are derived for two different forms of this problem; 1) when it is possible that the observation at any sample time contains signal or is noise alone, independent of the situation at any other sample, and 2) when the entire sequence of observations contains signals or is only noise.
640
Optimum Systems Control
Andrew P. Sage,Clive White,George M. Siouris +2 more
TL;DR: Optimum systems control is a topic related to agricultural information systems and focuses on controlling agricultural systems to achieve optimal performance.
602