Synchrosqueezing Transform in Biomedical Applications: A mini review

Duygu Degirmenci, Melike Yalcin, Mehmet Akif Ozdemir, A. Akan
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引用次数: 3

Abstract

Time-frequency representation (TFR) provides a good analysis for periodic signals; however, they are insufficient for nonstationary signals. The synchrosqueezing transform (SST) provides a strong analysis of nonstationary signals. The signal has different synchrosqueezing transformations that are implemented using different TFR. This paper provides a review of the different SST methods implemented using different TFR available in the literature, a comparison of these, and their use with different techniques in biomedical signal processing applications. Adding different techniques to the applied SST method affects the signal processing and classification ability of the selected SST method.
同步压缩变换在生物医学中的应用综述
时频表示(TFR)对周期信号提供了很好的分析;然而,它们对于非平稳信号是不够的。同步压缩变换(SST)为非平稳信号的分析提供了强有力的手段。信号具有使用不同TFR实现的不同同步压缩变换。本文综述了文献中使用不同TFR实现的不同SST方法,并对这些方法进行了比较,以及它们与不同技术在生物医学信号处理应用中的应用。在已应用的海表温度方法中加入不同的技术会影响所选海表温度方法的信号处理和分类能力。
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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