Detection and classification of noisy AR and ARMA processes

J. Tourneret, Karine Vareille, M. Coulon
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引用次数: 2

Abstract

The paper focuses on the detection and the classification of noisy AR and ARMA processes. These two kinds of processes cannot be distinguished by means of their second-order statistics, since they are Spectrally Equivalent (SE). Higher-order statistics are shown to be an efficient tool for their detection. A Neyman-Pearson (NP) test, based on these higher-order statistics, is then studied. The performance of the NP test provides a reference for comparing suboptimal detector performances.
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噪声AR和ARMA过程的检测与分类
本文主要研究了噪声AR和ARMA过程的检测与分类。这两种过程不能通过它们的二阶统计量来区分,因为它们是光谱等效的(SE)。高阶统计量被证明是检测它们的有效工具。然后研究了基于这些高阶统计量的Neyman-Pearson (NP)检验。NP测试的性能为比较次优检测器的性能提供了参考。
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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