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Extension of FBSE-EWT for Complex Signal Analysis

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posted on 2022-05-25, 20:38 authored by Aahan Tyagi, Vivek Kumar SinghVivek Kumar Singh, Ram Bilas Pachori
In this letter, a new framework based on Fourier- Bessel series expansion (FBSE)-empirical wavelet transform (EWT) is proposed with the aim of analyzing complex signals. The critical part of this framework is to separate the real- time equivalent positive and negative frequency components of complex signals using suitable filters and then decompose both the real-time signals into their corresponding intrinsic mode functions (IMFs) using the FBSE-EWT technique. After that, the obtained IMFs are represented in a set of complex IMFs (CIMFs) using the Hilbert transform. In the end, joint time-frequency distribution (TFD) is obtained using Hilbert spectral analysis of CIMFs. Two synthetic multicomponent complex signals are considered for simulation purposes, along with a real-world wind signal. The results of proposed framework compared with complex empirical mode decomposition (CEMD) and complex iterative eigenvalue decomposition of Hankel matrix (CIEVDHM) and found to be providing a better result.


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Indian Institute of Technology Indore

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  • India