Comparison and Application of Time-Frequency Analysis Methods for Nonstationary Signal Processing

被引：0

作者：

Zhu, Qiang ^{[1
]}

Wang, Yansong ^{[1
]}

Shen, Gongqi ^{[1
]}

机构：

[1] Shanghai Univ Engn Sci, Coll Automot Engn, Shanghai 201620, Peoples R China

来源：

ADVANCED RESEARCH ON COMPUTER EDUCATION, SIMULATION AND MODELING, PT I | 2011年 / 175卷

关键词：

Nonstationary signal; Short-time Fourier transform; Wavelet transform; Wigner-Ville distribution; Hilbert-Huang transform;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Most of signals in engineering are nonstationary and time-varying. The Fourier transform as a traditional approach can only provide the feature information in frequency domain. The time-frequency techniques may give a comprehensive description of signals in time-frequency planes. Based on some typical nonstationary signals, five time-frequency analysis methods, i.e., the short-time Fourier transform (STFT), wavelet transform (WT), Wigner- Ville distribution (WVD), pseudo-WVD (PWVD) and the Hilbert-Huang transform (HHT), were performed and compared in this paper. The characteristics of each method were obtained and discussed. Compared with the other methods, the HHT with a high time-frequency resolution can clearly describe the rules of the frequency compositions changing with time, is a good approach for feature extraction in nonstationary signal processing.

引用

页码：286 / 291

页数：6

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