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Karhunen-Loève Decomposition of Gaussian Measures on Banach Spaces

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Języki publikacji
EN
Abstrakty
EN
The study of Gaussian measures on Banach spaces is of active interest both in pure and applied mathematics. In particular, the spectra theorem for self-adjoint compact operators on Hilbert spaces provides a canonical decomposition of Gaussian measures on Hilbert spaces, the socalled Karhunen-Loève expansion. In this paper, we extend this result to Gaussian measures on Banach spaces in a very similar and constructive manner. In some sense, this can also be seen as a generalization of the spectral theorem for covariance operators associated with Gaussian measures on Banach spaces. In the special case of the standardWiener measure, this decomposition matches with Lévy-Ciesielski construction of Brownian motion.
Rocznik
Strony
279--297
Opis fizyczny
Bibliogr. 18 poz., wykr.
Twórcy
autor
  • Mines Saint-Étienne, Institut Fayol, Génie Mathématique et Industriel, LIMOS UMR 6158, 158 cours Fauriel, 42023 Saint-Étienne, France
  • Mines Saint-Étienne, Institut Fayol, Génie Mathématique et Industriel, LIMOS UMR 6158, 158 cours Fauriel, 42023 Saint-Étienne, France
Bibliografia
  • [1] N. Aronszajn, Theory of reproducing kernels, Trans. Amer. Math. Soc. 68 (1950), pp. 337-404.
  • [2] V. I. Bogachev, Gaussian Measures, American Mathematical Society, Providence, RI, 1998.
  • [3] G. Da Prato, An Introduction to Infinite-Dimensional Analysis, Springer, Berlin 2006.
  • [4] V. V. Fedorov, Theory of Optimal Experiments, Academic Press, New York-London 1972.
  • [5] M. Hairer, An Introduction to Stochastic PDEs, The University of Warwick / Courant Institute, Lecture notes, 2009.
  • [6] N. C. Jain and G. Kallianpur, Norm convergent expansions for Gaussian processes in Banach spaces, Proc. Amer. Math. Soc. 25 (1970), pp. 890-895.
  • [7] K. Karhunen, Über lineare Methoden in der Wahrscheinlichkeitsrechnung, Ann. Acad. Sci. Fenn. Ser. AI Math.-Phys. 37 (1947), pp. 1-79.
  • [8] J. Kuelbs, Expansions of vectors in a Banach space related to Gaussian measures, Proc. Amer. Math. Soc. 27 (1971), pp. 364-370.
  • [9] H.-H. Kuo, Gaussian Measures in Banach Spaces, Springer, Berlin-New York 1975.
  • [10] V. V. Kvaratskhelia, Unconditional convergence of functional series in problems of probability theory, J. Math. Sci. (N.Y.) 200 (2) (2014), pp. 143-294.
  • [11] S. Kwapień and B. Szymański, Some remarks on Gaussian measures in Banach spaces, Probab. Math. Statist. 1 (1) (1980), pp. 59-65.
  • [12] M. Loève, Probability Theory, second edition, D. Van Nostrand Co., Inc., Princeton, NJ, 1960.
  • [13] H. P. McKean Jr., Stochastic Integrals, Academic Press, New York 1969.
  • [14] C. E. Rasmussen and C. K. I. Williams, Gaussian Processes for Machine Learning, MIT Press, Cambridge, MA, 2006.
  • [15] L. Schwartz, Sous-espaces hilbertiens d’espaces vectoriels topologiques et noyaux associés (noyaux reproduisants), J. Anal. Math. 13 (1964), pp. 115-256.
  • [16] A. M. Stuart, Inverse problems: A Bayesian perspective, Acta Numer. 19 (2010), pp. 451-559.
  • [17] N. Vakhania, Canonical factorization of Gaussian covariance operators and some of its applications, Theory Probab. Appl. 38 (3) (1994), pp. 498-505.
  • [18] N. N. Vakhania, V. I. Tarieladze, and S. A. Chobanyan, Probability Distributions on Banach Spaces, D. Reidel Publishing Co., Dordrecht 1987.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-3bbd8e52-402b-488f-aa86-7c4bbecfb4c5
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