Nonlinear estimators of polynomials in mean values of a Gaussian stochastic process
Kybernetika, Tome 14 (1978) no. 3, pp. 206-220 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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Classification : 62M07, 62M09
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}
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Štulajter, František. Nonlinear estimators of polynomials in mean values of a Gaussian stochastic process. Kybernetika, Tome 14 (1978) no. 3, pp. 206-220. http://geodesic.mathdoc.fr/item/KYB_1978_14_3_a4/

[1] N. Aronszajn: Theory of Reproducing Kernels. Trans. Amer. Math. Soc.6S (1950), 337-404. | MR | Zbl

[2] D. L. Duttweiler T. Kailath: RKHS Approach to Detection and Estimation Problems - Part IV. Non Gaussian Detection. IEEE Trans. Inf. Th., IT-19 (1973), 19-28. | MR

[3] T. Kailath D. Duttweiler: An RKHS Approach to Detection and Estimation Problems - Part III. Generalized Innovations Representations and a Likelihood-Ratio Formula. IEEE Trans. Inf. Th., IT-18 (1972), 6, 730-745. | MR

[4] L. Duttweiler T. Kailath: RKHS Approach to Detection and Estimation Problems - Part V. Parameter Estimation. IEEE Trans. Inf. IT-19, (1973), 1, 29-37. | MR

[5] P. R. Halmos: Introduction to Hilbert space. Chelsea Publishing Company, New-York 1972.

[6] И. A. Ибрагимов Ю. A. Poзанов: Гауссовские случайные процессы. Hayкa, Mocквa 1970. | Zbl

[7] G. Kallianpur: The Role of RKHS in the Study of Gaussian Processes. In Advances in Probability, vol. 2, M. Dekker INC. New York 1970, 59-83. | MR

[8] E. Parzen: Statistical Inference on Time Series by Hilbert Space Methods. Technical report No 23, Stanford 1959. (Reprinted in the book E. Parzen: Time Series Analysis Papers. Holden-Day, San Francisco 1967.)

[9] E. Parzen: Statistical Inference on Time Series by RKHS Methods II. Proc. 12th Biennial Canadian Math. Congress, R. Pyke (Ed.), Providence, R. I.: Amer. Math. Soc. 1969, 1 - 37. | MR

[10] A. Pázman: Plans d'expérience pour les estimations de fonctionnelles non-linéaires. Annales de l'Institut H. Poincaré 13 (1977), No 3. | MR