Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144639
Title: Augmented EMD for complex-valued univariate signals
Authors: Oh, Beom-Seok
Zhuang, Huiping
Toh, Kar-Ann
Lin, Zhiping
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Oh, B.-S., Zhuang, H., Toh, K.-A., & Lin, Z. (2019). Augmented EMD for complex-valued univariate signals. IET Signal Processing, 13(4), 424-433. doi:10.1049/iet-spr.2018.5428
Journal: IET Signal Processing
Abstract: In this study, the authors propose an efficient extension of the standard empirical mode decomposition (EMD) for complex-valued univariate signal decomposition. The key idea of the extension is to convert a complex-valued univariate signal into a longer real-valued signal by augmenting the real part with the flipped imaginary part, and then to decompose it into intrinsic mode functions (IMFs) using the EMD once only. The bivariate IMFs are then retrieved from the obtained IMFs. Their empirical results on synthetic data show that the proposed method significantly outperforms the traditional bivariate EMD (BEMD) method in terms of computational efficiency while producing a comparable extraction error. Moreover, the proposed method shows better micro-Doppler signature analysis performance on physically measured continuous-wave radar data than that of the BEMD.
URI: https://hdl.handle.net/10356/144639
ISSN: 1751-9675
DOI: 10.1049/iet-spr.2018.5428
Rights: This paper is a postprint of a paper submitted to and accepted for publication in IET Signal Processing and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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