Fourier，Gabor，Morlet或Wigner：时频变换的比较
Fourier, Gabor, Morlet or Wigner: Comparison of Time-Frequency Transforms
摘要：
在数字信号处理中，时频变换用于分析时变信号相对于其随时间的频谱内容。除了常用的短时傅里叶变换外，文献中还存在其他方法，例如小波变换、Stockwell变换或Wigner-Ville变换。因此，从事数字信号处理任务的工程师经常面临这样的问题：哪种变换适合于特定的应用。为了解决这个问题，本文首先简要介绍了不同的转换。然后将它们与时间和频率上可实现的分辨率以及可能的伪影进行比较。最后，本文包含了来自不同应用领域的众多信号的时频表示的图库，以进行视觉比较。
英文摘要：
In digital signal processing time-frequency transforms are used to analyze time-varying signals with respect to their spectral contents over time. Apart from the commonly used short-time Fourier transform, other methods exist in literature, such as the Wavelet, Stockwell or Wigner-Ville transform. Consequently, engineers working on digital signal processing tasks are often faced with the question which transform is appropriate for a specific application. To address this question, this paper first briefly introduces the different transforms. Then it compares them with respect to the achievable resolution in time and frequency and possible artifacts. Finally, the paper contains a gallery of time-frequency representations of numerous signals from different fields of applications to allow for visual comparison.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
