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THE PROBLEM OF COMBINATORIAL ENCODING OF A CONTINUOUS DYNAMICS AND THE NOTION OF TRANSFER OF PATHS IN GRAPHS

机译:连续动态组合编码的问题及图表中路径转移概念的问题

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摘要

We introduce the notion of combinatorial encoding of continuous dynamical systems and suggest the first examples, which are the most interesting and important, namely, the combinatorial encoding of a Bernoulli process with continuous state space, e.g., a sequence of i.i.d. random variables with values in the interval with the Lebesgue measure (or a Lebesgue space).The main idea is to associate with a random object (a trajectory of the random process) a path in an â„•-graded graph and parametrize it with the vertices of the graph that belong to this path. This correspondence (encoding) is based on the definition of a decreasing sequence of cylinder partitions, and the first problem is to verify whether or not the given combinatorial encoding has the property of distinguishability, which means that our encoding is an isomorphism, or, equivalently, the limit of the increasing sequence of finite partitions is the partition into singletons mod 0. This is a generalization of the problem of generators in ergodic theory.The existence of a suitable â„•-graded graph is equivalent to the so-called standardness of the orbit partition in the sense of the theory of filtrations in measure spaces.In the last section, we define the notion of a so-called transfer, a transformation of paths in a graded graph, as a generalization of the shift in stationary dynamics.
机译:我们介绍了连续动态系统的组合编码的概念,并提出了第一示例,这是最有趣且重要的,即Bernoulli进程的组合编码,具有连续状态空间,例如,i.i.d的序列。随机值与Lebesgue测量(或lebesgue空间)的间隔中的随机变量。主要思想是将随机对象(随机过程的轨迹)关联,其中“的路径和与参数化属于该路径的图形的顶点。该对应关系(编码)基于汽缸分区的减少序列的定义,并且第一问题是验证给定的组合编码是否具有可区分性的性质,这意味着我们的编码是同构,或者等于的,有限分区的增加序列的极限是单板Mod 0的分区。这是ergodic理论中发电机的问题的概括。合适的②的存在等同于所谓的标准性在测量空间中的过滤理论意义上的轨道分区。在最后一节中,我们定义了所谓的传输的概念,分级图中的路径的转换,作为静止动力学的偏移的概括。

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  • 来源
    《Journal of Mathematical Sciences》 |2020年第5期|646-656|共11页
  • 作者

    A. M. Vershik;

  • 作者单位

    St.Petersburg Department of Steklov Institute of Mathematics and St.Petersburg State University St.Petersburg Russia Institute for Information Transmission Problems Moscow Russia;

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