TechRxiv
Unmarked_CFBSEEWT.pdf (776.37 kB)
Download file

Extension of FBSE-EWT for Complex Signal Analysis

Download (776.37 kB)
preprint
posted on 25.05.2022, 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.

History

Email Address of Submitting Author

phd1901102012@iiti.ac.in

ORCID of Submitting Author

0000-0001-7067-4850

Submitting Author's Institution

Indian Institute of Technology Indore

Submitting Author's Country

India