一类随机过程的多尺度建模

Multiscale Stochastic Modeling for a Random Process

基于多尺度随机模型具有有效性和高度并行算法这一优势,提出如何用三阶树多尺度模型来表示1-DReciprocal过程;并如何获得多尺度模型的参数.这就为具有Markov统计特性的信号或过程建立起一般的三阶树多尺度随机模型,为更有效的解决实际问题提供了理论基础.同时,给出了一类定义在单位区间上的随机过程三阶树多尺度表示的仿真示例.

In this paper, based on an extremely efficient and highly parallelizable algorithm for optimal estimate of multiscale stochastic model, we develop how the multiscale model of third-order tree can be used to represent 1-D Reciprocal process, and how the parameters of multiscale stochastic model can be obtained. Therefore, a more general third-order tree multiscale stochastic model is constructed for the signal and process that have Markovian, which in turn provides the theoretic basis for solution of the practical problems. At the same time, the computer simulation about the three-order tree multiscale representation of a class of stochastic process defined the unit interval.