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Lo, James Ting-Ho

On optimal nonlinear estimation. II: Discrete observation. (English) Zbl 0277.93013

Inf. Sci. 7, 1-10 (1974).
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MSC:

93E10 Estimation and detection in stochastic control theory
62F10 Point estimation
94A05 Communication theory
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[1] Lo, J. T., Information Sciences, 6, 19-32 (1973) · Zbl 0255.93024
[2] Bucy, R. S.; Joseph, P. D., Filtering for Stochastic Processes with Application to Guidance (1968), Interscience: Interscience New York · Zbl 0174.21903
[3] Lo, J. T., On optimal nonlinear estimation-Part II: discrete observation, (Proc. 1970 IEEE Symp. Adaptive Processes (9th). Proc. 1970 IEEE Symp. Adaptive Processes (9th), Decision and Control (1970)), 2.1-2.4
[4] Lo, J. T., IEEE Trans. IT-18, No. 5, 583-588 (1972) · Zbl 0246.93042
[5] Sorenson, H. W.; Alspach, D. L., Gaussian approximations for nonlinear filtering, (Proc. 1970 IEEE Symp. Adaptive Processes (9th). Proc. 1970 IEEE Symp. Adaptive Processes (9th), Decision and Control (1970)), 3.1-3.9 · Zbl 0219.93027
[6] Lainiotis, D. G.; Park, S. K.; Krishnaiah, R., Optimal state-vector, Trans. IEEE, AC-16, 2, 197-198 (1971)
[7] Bucy, R. S., Nonlinear filtering theory, IEEE Trans., AC-10, 198 (1965)
[8] Ho, Y. C.; Lee, R. C.K., A Bayesian approach to problems in stochastic estimation and control, IEEE Trans. Automatic Control, 333-339 (1964)
[9] Jazwinski, A. H., Nonlinear filtering with discrete observations, (AIAA 3rd Aerospace Sciences Meeting. AIAA 3rd Aerospace Sciences Meeting, New York (1966)), Paper No. 66-38
[10] Kaiman, R. E., A new approach to linear filtering and prediction problems, J. Basic Engineering, 82, 34-45 (1960)
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