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References:
[1] V. Peterka: Bayesian approach to system identification. In: Trends and Progress in System Identification (P. Eykhoff, ed.), Pergamon Press, Oxford 1981. MR 0746139
[2] A. H. Jazwinski: Stochastic Processes and Filtering Theory. Academic Press, New York 1970. Zbl 0203.50101
[3] H. W. Sorenson, A. R. Stubberud: Non-linear filtering by approximation of the a poste- riori density. Internat. J. Control 8 (1968), 33-51.
[4] K. Srinivasan: State estimation by orthogonal expansion of probability distributions. IEEE Trans. Automat. Control AC-15 (1970), 3-10.
[5] R. S. Bucy, K. D. Senne: Digital synthesis of non-linear filters. Automatica 7 (1971), 287-298. Zbl 0269.93070
[6] H. W. Sorenson, D. L. Alspach: Recursive Bayesian estimation using Gaussian sums. Automatica 7 (1971), 465-479. MR 0321581 | Zbl 0219.93020
[7] D. L. Alspach: Gaussian sum approximations in nonlinear filtering and control. In: Esti- mation Theory (D. G. Lainiotis, ed.), American Elsevier, New York 1974. MR 0368877 | Zbl 0291.93053
[8] J. L. Center: Practical nonlinear filtering of discrete observations by generalized least- squares approximation of the conditional probability distribution. In: Proc. of 2nd Symp. on Nonlinear Estimation, San Diego 1971.
[9] R. J. P. de Figueiredo, J. G. Jan: Spline filters. In: Proc. of 2nd Symp. on Nonlinear Estimation, San Diego 1971.
[10] D. G. Lainiotis, J. G. Deshpande: Parameter estimation using splines. In: Estimation Theory (D. G. Lainiotis, ed.), American Elsevier, New York 1974. MR 0366480 | Zbl 0309.62072
[11] H. W. Sorenson: On the development of practical nonlinear filters. In: Estimation Theory (D. G. Lainiotis, ed.), American Elsevier, New York 1974. MR 0363605 | Zbl 0291.93052
[12] A. H. Wang, R. L. Klein: Implementation of nonlinear estimators using monospline. In: Proc. of 13th IEEE Conf. on Decision and Control, 1976.
[13] D. V. Lindley: Approximate Bayesian methods. In: Bayesian Statistics (J. M. Bernardo. M. H. DeGroot, D. V, Lindley and A. F. M. Smith, eds.), University Press, Valencia 1980. MR 0638879 | Zbl 0458.62002
[14] O. L. R. Jacobs: Recursive estimation for non-linear Wiener systems by on-line implementation of Bayes' rule. Trans. Inst. M. C. 7 (1985), 245-250.
[15] M. Karny, K. M. Hangos: Approximation of the Bayes rule. In: Proc. of 7th IFAC/ IFORS Symp. on Identification and System Parameter Estimation, York 1985.
[16] A. R. Stubberud, G. H. Xia: A fixed complexity nonlinear estimation technique. In: Proc. of 25th Conf. on Decision and Control, Athens 1986.
[17] M. Karny, K. M. Hangos: One-sided approximation of Bayes rule: theoretical background. In: Proc. of 10th IFAC Congress, Munich 19S7.
[18] S. C. Kramer, H. W. Sorenson: Bayesian parameter estimation. In: Proc. of 1987 Amer. Control. Conf., Minneapolis 1987.
[19] J. M. Bernardo: Approximations in statistics from a decision theoretical viewpoint. In: Probability and Bayesian Statistics (R. Viertl, ed.), Plenum Press, New York 1987. MR 0925441
[20] B. de Finetti: Theory of Probability: A Critical Introductory Treatment. Wiley, New York 1970 (Vol. 1), Chichester 1972 (Vol. 2).
[21] I. J. Good: The Estimation of Probabilities: An Essay on Modern Bayesian Methods. MIT Press, Cambridge 1965. MR 0185724 | Zbl 0168.39603
[22] I. J. Good: Some history of the hierarchical Bayesian methodology. In: Bayesian Statistics (J. M. Bernardo, M. H. DeGroot, D. V. Lindley and A. F. M. Smith, eds.), University Press, Valencia 1980. MR 0638884 | Zbl 0467.62002
[23] N. N. Chentsov: Statistical Decision Rules and Optimal Inference (in Russian). Nauka, Moscow 1972, English translation: Translation of Mathematcal Monographs, 53, AMS, Rhode Island 1982. MR 0343398
[24] R. Larsen: Functional Analysis: An Introduction. Dekker, Ner York 1973. MR 0461069 | Zbl 0261.46001
[25] R. Kulhavý: A Bazes-closed approximation of recursive nonlinear estimation. Internat. J. Adaptive Control and Signal Processing (submitted).
[26] L. J. Savage: The Foundations of Statistics. Wiley, New York 1954. MR 0063582 | Zbl 0055.12604
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