基于轴邻比较的ARMA模型排序新算法

Khaled E. Al-Qawasmi, A. Al-Smadi, A. Al-Hamami
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引用次数: 0

摘要

本文提出了一种基于四舍五入的ARMA模型阶数确定新算法,该算法针对二进制词的精度问题进行了实现。四舍五入的方法使用了地板和天花板函数。所提出的算法基于从Liang等人[6]开发的众所周知的最小特征值(MEV)方法中选择一系列枢轴单元值。它使用枢轴单元格值的下限和上限函数及其邻居的值来搜索包含真阶估计的角。观察到的序列可能受到加性高斯噪声的污染。仿真实例说明了该方法在不同信噪比下的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new algorithm for the ARMA model order via pivot-neighbors comparisons
This paper presents a new algorithm for the determination of the ARMA model orders based on a rounding approach which is implemented to deal with the precision of binary words. The rounding approach uses the floor and the ceiling functions. The proposed algorithm is based on selecting a sequence of pivot cells values from the well known minimum eigenvalue (MEV) method developed by Liang et. al. [6]. It uses the floor and the ceiling functions of the pivot cells values and the values of its neighbors to search for the corner that contains the estimates of the true orders. The observed sequence may be contaminated by additive Gaussian noise. Simulation examples are given to illustrate the effectiveness of the proposed technique for different signal to noise ratios.
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