7 October 2016 EMD-WVD time-frequency distribution for analysis of multi-component signals
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Proceedings Volume 9902, Fourth International Conference on Wireless and Optical Communications; 99020W (2016) https://doi.org/10.1117/12.2262260
Event: Fourth International Conference on Wireless and Optical Communications, 2016, Beijing, China
Abstract
Time-frequency distribution (TFD) is two-dimensional function that indicates the time-varying frequency content of one-dimensional signals. And The Wigner-Ville distribution (WVD) is an important and effective time-frequency analysis method. The WVD can efficiently show the characteristic of a mono-component signal. However, a major drawback is the extra cross-terms when multi-component signals are analyzed by WVD. In order to eliminating the cross-terms, we decompose signals into single frequency components – Intrinsic Mode Function (IMF) – by using the Empirical Mode decomposition (EMD) first, then use WVD to analyze each single IMF. In this paper, we define this new time-frequency distribution as EMD-WVD. And the experiment results show that the proposed time-frequency method can solve the cross-terms problem effectively and improve the accuracy of WVD time-frequency analysis.
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Yunzi Chai, Xudong Zhang, "EMD-WVD time-frequency distribution for analysis of multi-component signals", Proc. SPIE 9902, Fourth International Conference on Wireless and Optical Communications, 99020W (7 October 2016); doi: 10.1117/12.2262260; https://doi.org/10.1117/12.2262260
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