Recognition of non-Gaussian signals against a background of noise using higher order statistics

N. Kudriavtseva, V. Tykhonov, K. Netrebenko
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引用次数: 3

Abstract

The aim of the paper is to study the possibility of advancing noised non-Gaussian processes recognition using the features based on higher-order statistics. Several new recognition features based on the higher-order statistics, the basis of advancing recognition results in the presence of noise, decision rules and recognition system frameworks we proposed in the paper. The efficiency test of the proposed method is performed by statistical modeling. We proposed features of recognition based on the third-order statistics.
利用高阶统计量对噪声背景下的非高斯信号进行识别
本文的目的是研究利用基于高阶统计量的特征推进有噪非高斯过程识别的可能性。本文提出了基于高阶统计量的几种新的识别特征,并在此基础上对噪声、决策规则和识别系统框架进行了改进。通过统计建模验证了该方法的有效性。我们提出了基于三阶统计量的特征识别。
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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