Extraction and Separation of Nonstationary Signals in Different Linear Mixed Models Based on Time-Frequency Analysis

DOI

10.2991/icmcs-18.2018.125How to use a DOI?

Keywords

Time-Frequency analysis; Linear mixed model; Non-Stationary signal

Abstract

Nonstationary signal analysis and processing are widely used in noise reduction, feature extraction, state recognition, fault diagnosis and other fields. The general methods include time domain analysis, frequency domain analysis and time-frequency combined analysis. Time frequency analysis is an ideal signal analysis method. In this paper, the definition and idea of time-frequency analysis are introduced. Short-time Fourier Transform (STFT) and wavelet transform (WT) linear hybrid models for time-frequency analysis are described. Finally, the future development of time-frequency analysis is introduced.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hui Zhang
PY  - 2018/10
DA  - 2018/10
TI  - Extraction and Separation of Nonstationary Signals in Different Linear Mixed Models Based on Time-Frequency Analysis
BT  - Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018)
PB  - Atlantis Press
SP  - 606
EP  - 608
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmcs-18.2018.125
DO  - 10.2991/icmcs-18.2018.125
ID  - Zhang2018/10
ER  -