基于增强双MA模型的ARMA参数估计

Achilleas C. Stogioglou, S. Mclaughlin
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引用次数: 0

摘要

研究了ΜΛ累积增强法在不可观测独立同分布(IID)非高斯过程激励下非最小相位ARMA(p, q)系统参数辨识中的应用。本文提出的方法是基于[1]的双MA方法。利用累积量增强对原始ARMA(p, q)模型分解后的两个中间MA模型的累积量进行了改进。仿真结果证明了累积增强对估计ARMA参数的影响。
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ARMA parameter estimation through enhanced double MA modelling
This paper considers the application of ΜΛ cumulant enhancement to the identification of the parameters of a causal nonminimum phase ARMA(p, q) system which is excited by an unobservable independent identically distributed (IID) non-Gaussian process. The method proposed in this paper is based on the double MA method of [l]. The cumulant enhancement is used to improve the cumulante of the two intermediate MA models which result from the decomposition of the original ARMA(p, q) model. Simulation results are presented to demonstrate the effects of cumulant enhancement on the estimated ARMA parameters.
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