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arXiv 2008.11050math.PR
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非平稳马氏相关矩阵乘积的指数增长性

Exponential growth of products of non-stationary Markov-dependent matrices

Ilya Goldsheid

摘要:

设$(ξ_j)_{j\ge1} $是具有相空间$X$的非平稳马尔可夫链,并且设$\mathfrak{g}_j:\,X\mapsto\mathrm{SL}(m,\mathbb{R})$是$X$上的值在幺模群中的函数序列。设置$g_j=\mathfrak{g}_j(ξ_j)$,并用$S_n=g_n\ldots g_1$表示矩阵$g_j$的乘积。当马尔可夫链不是平稳的时,我们给出了范数$\|S_n\|$指数增长性的充分条件。这推广了Furstenberg关于独立同分布矩阵乘积的指数增长性的经典定理以及Virtser将其推广到平稳马氏相依矩阵乘积的结果.

英文摘要:

Let $(ξ_j)_{j\ge1} $, be a non-stationary Markov chain with phase space $X$ and let $\mathfrak{g}_j:\,X\mapsto\mathrm{SL}(m,\mathbb{R})$ be a sequence of functions on $X$ with values in the unimodular group. Set $g_j=\mathfrak{g}_j(ξ_j)$ and denote by $S_n=g_n\ldots g_1$, the product of the matrices $g_j$. We provide sufficient conditions for exponential growth of the norm $\|S_n\|$ when the Markov chain is not supposed to be stationary. This generalizes the classical theorem of Furstenberg on the exponential growth of products of independent identically distributed matrices as well as its extension by Virtser to products of stationary Markov-dependent matrices.

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