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High-concentration time-frequency analysis for multi-component nonstationary signals based on combined multi-window Gabor transform

机译:基于组合多窗口Gabor变换的多分量非平稳信号高集中时频分析

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摘要

Purpose This study aims to reveal the essential characteristics of nonstationary signals and explore the high-concentration representation in the joint time-frequency (TF) plane. Design/methodology/approach In this paper, the authors consider the effective TF analysis for nonstationary signals consisting of multiple components. Findings To make it, the authors propose the combined multi-window Gabor transform (CMGT) under the scheme of multi-window Gabor transform by introducing the combination operator. The authors establish the completeness utilizing the discrete piecewise Zak transform and provide the perfect-reconstruction conditions with respect to combined TF coefficients. The high-concentration is achieved by optimization. The authors establish the optimization function with considerations of TF concentration and computational complexity. Based on Bergman formulation, the iteration process is further analyzed to obtain the optimal solution. Originality/value With numerical experiments, it is verified that the proposed CMGT performs better in TF analysis for multi-component nonstationary signals.
机译:目的 揭示非平稳信号的本质特征,探索联合时频(TF)平面上的高浓度表示。设计/方法/途径 在本文中,作者考虑了由多个分量组成的非平稳信号的有效TF分析。研究结果 为此,作者通过引入组合算子,提出了多窗口Gabor变换方案下的组合多窗口Gabor变换(CMGT)。作者利用离散分段 Zak 变换建立了完备性,并提供了关于组合 TF 系数的完美重构条件。通过优化实现高浓度。作者在考虑TF浓度和计算复杂度的情况下建立了优化函数。基于Bergman公式,进一步分析迭代过程,得到最优解。独创性/价值 通过数值实验验证了所提出的CMGT在多分量非平稳信号的TF分析中表现更好。

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