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研究生: 江鎮宇
Chen-Yu Chiang
論文名稱: 關於φ-Subgaussian隨機變數數列收斂之研究
A Study on Convergence Theorems for Sums of φ-Subgaussian Random Variables
指導教授: 胡殿中
Tien-Chung Hu
口試委員:
學位類別: 碩士
Master
系所名稱: 理學院 - 數學系
Department of Mathematics
論文出版年: 2007
畢業學年度: 95
語文別: 英文
論文頁數: 16
中文關鍵詞: φ-subgaussian隨機變數幾近收斂
外文關鍵詞: φ-subgaussian random variable, Almost sure convergence
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  • 在這篇論文中,我們會提供一個充分條件使得級數 T_n=a_{n1}*X_1+a_{n2}*X_2+...+a_{nk}*X_k+...幾近收斂,其中{X_k,k=1,2,
    ...}為一φ-subgaussian隨機變數數列。另外,我們會探討有關傅立葉分析的主題。實際上,我們會證明級數 a_1*X_1*cos(t+D_1)+...+a_n*X_n*cos(nt+D_n)+...,0≦t≦2π 幾近收斂到一個隨機過程 f(t),0≦t≦2π,其中{X_n,n=1,2,...}仍然為一φ-subgaussian 隨機變數數列,而{D_n,n=1,2,...}為一任意的隨機變數數列。


    In this thesis we give a sufficient condition for the almost sure convergence of weighted sums of T_n=a_{n1}*X_1+a_{n2}*X_2+...+a_{nk}*X_k+... , where {X_k,k=1,2,...} be a sequence of φ-subgaussian random variables. Further-more, an application to the Fourier analysis is given. More
    precisely, let {X_n,n=1,2,...} be a sequence of φ-subgauss-
    ian random variables and {D_n,n=1,2,...} be an arbitrary
    sequence of random variables. We consider the convergence
    of the series a_1*X_1*cos(t+D_1)+...+a_n*X_n*cos(nt+D_n)+
    ...,0≦t≦2π to a stochastic process f(t),0≦t≦2π.

    1.Introduction (p1) 1.1 Weighted Sums of Random Variable (p1) 1.2 Convergence for Series of Generalized Sub-gaussian R.V.'s (p1) 1.3 About Fourier Analysis (p3) 1.4 In This Thesis (p3) 2. Preliminaries (p4) 2.1 Orlicz N-function φ(x) (p4) 2.2 Complementary N-function φ*(x) (p6) 2.3 φ-Subgaussian Random Variables and Its Properties (p7) 2.4 Some Other Lemmas (p10) 3. Convergence Theorems for φ-Subgaussian R.V.'s (p11) 3.1 Convergence of Weighted Sums (p11) 3.2 Application to Fourier Analysis (p12) 4. Conclusion (p15) References (p16)

    [1] Antonini, R.G., Hu, T-C. and Volodin, A., 2006. On the concentration phenomenon for φ-subgaussian random elements. Statistics & Probability Letters. 76, 465-469.
    [2] Antonini, R.G., Kozachenko, Y. and Volodin, A., 2007. Convergence of series of dependent φ-subgaussian random variables. J. Math. Anal. Appl.
    [3] Buldygin, V.V., Kozachenko and Yu.V., 2000. Metric Characterization of Random Variables and Random Processes. American Mathematical Society, Providence, RI.
    [4] Chow, Y.S., 1966. Some convergence theorems for independent random variables. Ann. Math. Statist. 37, 1482-1493.
    [5] Giuliano Antonini, R., Kozachenko, Yu. and Nikitina, T., 2003. Spaces of φ-sub-Gaussian random variables. Rend. Accad. Naz. Sci. XL Mem. Mat. Appl. 27(5), 95-124.
    [6] Hill, J.D., 1949. The Borel property of summability methods. Pacific J. Math. 1399-1409.
    [7] Krasnoselsky, M.A. and Rutitsky, Y.B., 1961. Convex functions and Orlicz spaces. Noordhof, Gröningen.
    [8] Taylor, R.L. and Hu, T-C., 1987. Sub-gaussian techniques in proving strong laws of large numbers. Amer. Math. Monthly, 295-299.
    [9] Zygmund, A., 2002. Trigonometric series. Vol. II. 3-rd edition. Cambridge Mathematical Library. Cambridge University Press, Cambridge.

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