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Recursive Bayesian estimation using Gaussian sums. (English) Zbl 0219.93020

93E10 Estimation and detection in stochastic control theory
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[1] Jazwinski, A.H., Stochastic processes and filtering theory, (1970), Academic Press New York · Zbl 0203.50101
[2] Kalman, R.E., A new approach to linear filtering and prediction problems, J. bas. engng, 82D, 35-45, (1960)
[3] Sorenson, H.W., (), Ch. 5
[4] Cosaert, R.; Gottzein, E., A decoupled shifting memory filter method for radio tracking of space vehicles, ()
[5] Jazwinski, A., Adaptive filtering, Automatica, 5, 475-485, (1969) · Zbl 0214.47304
[6] Ho, Y.C.; Lee, R.C.K., A Bayesian approach to problems in stochastic estimation and control, IEEE trans. aut. control, 9, 333-339, (1964)
[7] Kushner, H.J., On the differential equations satisfied by conditional probability densities of Markov processes, SIAM J. control, 2, 106-119, (1964) · Zbl 0131.16602
[8] Fisher, J.R.; Stear, E.B., Optimal non-linear filtering for independent increment processes, parts I and II, IEEE trans. inform. theory, 3, 558-578, (1967) · Zbl 0168.40401
[9] Aoki, M., Optimization of stochastic systems, topics in discrete-time systems, (1967), Academic Press New York · Zbl 0168.15802
[10] Sorenson, H.W.; Stubberud, A.R., Nonlinear filtering by approximation of the a posteriori density, Int. J. control, 18, 33-51, (1968) · Zbl 0176.08302
[11] Aoki, M., Optimal Bayesian and MIN-MAX control of a class of stochastic and adaptive dynamic systems, (), 77-84
[12] Cameron, A.V., Control and estimation of linear systems with Nongaussian a priori distributions, ()
[13] Lo, J.T., Finite dimensional sensor orbits and optimal nonlinear filtering, () · Zbl 0246.93042
[14] Koreyaar, J., (), 330-333
[15] Feller, W., (), 249
[16] Spragins, J.D., Reproducing distributions for machine learning, ()
[17] Alspach, D.L., A Bayesian approximation technique for estimation and control of time-discrete stochastic systems, () · Zbl 0351.93036
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