谐波小波变换信号分解与改进Wigner-Ville分布的修正群延迟

S. Narasimhan, B. Kumar
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引用次数: 4

摘要

提出了一种基于谐波小波变换(SDHWT)信号分解和修正幅度群延迟函数(MMGD)的Wigner-Ville分布(WVD)新方法。SDHWT直接提供子带信号,并将这些分量的WVD连接起来得到整体WVD,而不使用抗混叠和图像抑制滤波。SDHWT和MMGD分别在不应用任何窗口的情况下去除交叉项(CT)的存在和由于WVD内核截断而引起的涟漪效应。由于没有时间和频率平滑,该方法在时间和频率分辨率以及时频表示(TFR)方面都比伪WVD (PWVD)有更好的性能。此外,与PWVD相比,它具有相对更好的抗噪性。在WVD中,对于信号分解,与使用滤波器组相比,使用SDHWT提供了几乎相似的结果,但具有显着(72%)的计算优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harmonic wavelet transform signal decomposition and modified group delay for improved Wigner-Ville distribution
A new approach for the Wigner-Ville distribution (WVD) based on signal decomposition by harmonic wavelet transform (SDHWT) and the modified magnitude group delay function (MMGD) has been proposed. The SDHWT directly provides subband signals and the WVD of these components are concatenated to get the overall WVD without using antialias and image rejection filtering. The SDHWT and the MMGD remove the existence of crossterms (CT) and the ripple effect due to truncation of the WVD kernel without applying any window, respectively. Since there is no time and frequency smoothing, the proposed method has a better performance in terms of both time and frequency resolution and desirable properties of a time-frequency representation (TFR) than the pseudo WVD (PWVD). Further, it has a relatively better noise immunity compared to that of PWVD. In the WVD, for signal decomposition, the use of SDHWT, compared to that of a filter bank, provides almost similar results but has a significant (72%) computational advantage.
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