(几乎)周期移动平均系统辨识的线性代数方法

Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1997-07-21 DOI:10.1109/HOST.1997.613498

Ying-Chang Liang, A. R. Leyman, Xianda Zhang

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引用次数: 1

摘要

本文研究(几乎)周期移动平均(APMA)系统的辨识问题。利用测量值的时变高阶累积量建立了两个正态方程，并在此基础上提出了两种新的参数估计线性代数算法。仿真实例验证了这些新方法的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Linear algebraic approaches for (almost) periodic moving average system identification

This paper addresses the problem of (almost) periodic moving average (APMA) system identification. Two normal equations are established by using time varying higher order cumulants of the measurements, from which two new linear algebraic algorithms are presented for parameter estimation. Simulation examples are given to demonstrate the performance of these new approaches.

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Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics

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