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Accuracy of discrete Markov approximation in the problems of estimation of random processes characteristics

机译:随机过程特征估计问题中离散马尔可夫近似的精度

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摘要

Many computational algorithms related to Markov processes contain the covariance matrix of measurements. Approximation of covariance matrix of measurements of observed random process by the covariance matrix of Markov process is of great interest. Because it gives an opportunity to develop computationally efficient algorithms for analysis of Markov processes (parametric identification, filtering, interpolation and others). This paper presents the algorithm of approximation of the covariance matrix of the observed process by the covariance matrix of a multiply connected (m-connected) Markov process. It has been shown that for many problems such approximation provides necessary accuracy.
机译:与马尔可夫过程有关的许多计算算法都包含测量的协方差矩阵。马尔可夫过程的协方差矩阵对观测到的随机过程的测量值的协方差矩阵的逼近引起了人们的极大兴趣。因为它为开发用于计算马尔可夫过程(参数识别,滤波,插值等)的高效计算算法提供了机会。本文提出了一个由多连接(m-连接)马尔可夫过程的协方差矩阵近似所观察过程的协方差矩阵的算法。已经表明,对于许多问题,这种近似提供了必要的精度。

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