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A Novel Method of Identifying Threshold for Gabor Transform Filter based on Inter-cluster Distance Probability

机译:基于簇间距离概率的Gabor变换滤波器阈值识别新方法

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Gabor transform suitable for time-frequency analysis and good for filtering non-stationary signals. The threshold of the Gabor transform filter is a key factor for the filter's effectiveness. The popularly used threshold obtained by linear method is not suitable for non-stationary signals with low signal to noise ratio (SNR) because, it cannot separate the expansion coefficients of noise and useful signals, hi this paper, a novel method to identify Gabor transform filter's threshold based on initial highest inter-cluster distance probability is proposed. Simulation experiments have been carried out under several conditions. The experimental results show that the proposed threshold is highly suitable, especially when the signal's SNR is very low and the filter output is very consistent to the real original signal and keeps no pseudo signal in zero regions.
机译:Gabor变换适用于时频分析,并且适合过滤非平稳信号。 Gabor变换滤波器的阈值是滤波器有效性的关键因素。通过线性方法获得的普遍使用的阈值不适用于具有低信噪比(SNR)的非平稳信号,因为它无法分离噪声和有用信号的扩展系数。在本文中,一种识别Gabor变换的新方法提出了基于初始最大簇间距离概率的滤波器阈值。模拟实验已经在几种条件下进行了。实验结果表明,提出的阈值非常适合,特别是在信号的SNR非常低且滤波器输出与真实的原始信号非常一致且零区域不保留任何伪信号的情况下。

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