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Previous article Next article A Functional Limit Theorem for Stationary Processes: A Martingale ApproachD. O. ChikinD. O. Chikinhttps://doi.org/10.1137/1134083PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] Patrick Billingsley, Convergence of probability measures, John Wiley & Sons Inc., New York, 1968xii+253 38:1718 0172.21201 Google Scholar[2] Walter Philipp and , William Stout, Almost sure invariance principles for partial sums of weakly dependent random variables, Mem. Amer. Math. Soc. 2, (1975), iv+140 55:6570 0361.60007 CrossrefGoogle Scholar[3] I. A. Ibragimov and , Yu. V. Linnik, Independent and stationary sequences of random variables, Wolters-Noordhoff Publishing, Groningen, 1971, 443– 48:1287 0219.60027 Google Scholar[4] P. Crepel, Variables aléatoires dépendantsOutils et modèles mathématiques pour 1'automatique: L'analyse de systèmes et le traitement du signal, Vol. 1, Hermann, Paris, 1981, 565–592 0479.60008 Google Scholar[5] P. 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Shiryayev, Probability, Graduate Texts in Mathematics, Vol. 95, Springer-Verlag, New York, 1984xi+577, Berlin 85a:60007 0536.60001 CrossrefGoogle Scholar Previous article Next article FiguresRelatedReferencesCited byDetails On the Rate of Convergence of Solution of Differential Equation Disturbed by “Physical” White Noise to a Solution of Appropriate Diffusion Equation. Exponential MixingB. V. Bondarev and S. M. Kozyr15 November 2012 | Theory of Probability & Its Applications, Vol. 56, No. 4AbstractPDF (224 KB)Martingale approximations for continuous-time and discrete-time stationary Markov processesStochastic Processes and their Applications, Vol. 115, No. 9 Cross Ref The central limit theorem for stationary Markov processes with normal generator—with applications to hypergroups20 August 2006 | Stochastics, Vol. 77, No. 4 Cross Ref On the Kolmogorov--Hajek--Rényi Inequality for Normed Integrals of Weakly Dependent ProcessesB. V. 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