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Analysis of local time-frequency entropy features for nonstationary signal components time supports detection

机译:非平稳信号分量时间支持的局部时频熵特征分析

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Identification of different specific signal components, produced by one or more sources, is a problem encountered in many signal processing applications. This can be done by applying the local time-frequency-based Renyi entropy for estimation of the instantaneous number of components in a signal. Using the spectrogram, one of the most simple quadratic time-frequency distributions, the paper proves the local applicability of the counting property of the Renyi entropy. The paper also studies the influence of the entropy order and spectrogram parameters on the estimation results. Numerical simulations are provided to quantify the observed behavior of the local entropy in the case of intersecting components. The causes of decrements in the local number of time supports in the time-frequency plane are also studied. Finally, results are provided to illustrate the findings of the study and its potential use as a key step in multicomponent instantaneous frequency estimation. (C) 2014 Elsevier Inc. All rights reserved.
机译:由一个或多个源产生的不同特定信号分量的识别是许多信号处理应用程序中遇到的问题。这可以通过应用基于局部时频的Renyi熵来估计信号中的瞬时分量来完成。利用最简单的二次时频分布频谱图,证明了仁义熵计数性质的局部适用性。本文还研究了熵阶和谱图参数对估计结果的影响。提供了数值模拟,以量化在相交的情况下局部熵的观测行为。还研究了时频平面中本地时间支持量减少的原因。最后,提供结果以说明研究结果及其潜在用途,作为多分量瞬时频率估计中的关键步骤。 (C)2014 Elsevier Inc.保留所有权利。

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