独立的m维实随机过程均方极限的独立性
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摘要
介绍了两个m维实随机向量序列相互独立时,其均方收敛的结果间仍具有相互独立性,并将此结论推广到任意有限维的两个实随机向量序列,以及任意有限维的两个连续参数实随机过程上去.
It is proved that the mean square limits of two independent m-dimensional real stochastic vertor sequences are still independent.And the result was generalized to the case of finite-dimensional real stochastic vertor sequences and finitedimensional real stochastic processes with continuous parameters.
It is proved that the mean square limits of two independent m-dimensional real stochastic vertor sequences are still independent.And the result was generalized to the case of finite-dimensional real stochastic vertor sequences and finitedimensional real stochastic processes with continuous parameters.
引文
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[13]孙洪祥.随机过程[M].北京:机械工业出版社,2008.
[14]吴让泉,胡良剑.二阶模糊随机过程的均方收敛性及其应用[J].数理统计与应用概率,1998,13(3):175-182.
[15]袁野.不确定变量序列r阶收敛与二重收敛[D].苏州:苏州科技学院,2014:6.
[2]Bradley R C.On the spectral density and asymptotic normality of weakly dependent random fields[J].J Theor Probab,1992,5:355-373.
[3]Bradley R C.Equivalent mixing conditions for random fields[J].Ann Probab,1993,21:1921-1926.
[4]Bryc W,Smolenski W.Moment conditions for almost sure convergence of weakly correlated random variables[J].Proc Amer Math Soc,1993,119:629-635.
[5]吴群英,林亮.φ~混合序列的完全收敛性和强收敛性[J].工程数学学报,2004,21(1):75-80.
[6]黄海午,王定成,吴群英.φ~混合随机变量序列的强收敛定律(英文)[J].应用概率统计,2012,28(2):181-188.
[7]邱德华.ρ~混合随机变量加权和的收敛性[J].数学物理学报,2011,31A(1):132-141.
[8]毛用才,胡奇英.随机过程[M].西安:西安电子科技大学出版社,2002.
[9]张卓奎,陈慧婵.随机过程[M].西安:西安电子科技大学出版社,2003.
[10]尹国举,朱建华.二阶矩模糊随机过程的均方收敛性[J].模糊系统与数学,2001,15(2):65-67.
[11]刘建平,王洪林.二阶矩模糊随机过程的均方收敛性[J].河北工程技术高等专科学校学报,2002,3:58-60.
[12]王进波.时标上的随机分析及应用[D].广东:广东工业大学,2008:5.
[13]孙洪祥.随机过程[M].北京:机械工业出版社,2008.
[14]吴让泉,胡良剑.二阶模糊随机过程的均方收敛性及其应用[J].数理统计与应用概率,1998,13(3):175-182.
[15]袁野.不确定变量序列r阶收敛与二重收敛[D].苏州:苏州科技学院,2014:6.