An advanced method to estimate parameters of piecewise stationary stochastic process
一种改进的分段平稳随机过程的参数估计方法

A new way to analysis nonstationary stochastic process is to divide it into piece-wise stationary stochastic process. Djuric(1992) used Bayes method to estimate the parameters, which can optimally divide the nonstationary stochastic process into stationary stochastic process. Some authors estimated the optimum parameters through calculating recursively the multivariate conditional likelihood function, which made the computation very complex. Basing on some natural characteristics of Aft mode, a new recursive method is provided, which can improve the computation efficiently, to estimate the optimum parameters.