Malik, Qasim Waheed and ur Rehman, Naveed and Gull, Sikender and Ehsan, Shoaib and McDonald-Maier, Klaus (2019) FPGA based real-time implementation of Bivariate Empirical Mode Decomposition. Circuits, Systems, and Signal Processing, 38 (1). pp. 118-137. DOI https://doi.org/10.1007/s00034-018-0844-2
Malik, Qasim Waheed and ur Rehman, Naveed and Gull, Sikender and Ehsan, Shoaib and McDonald-Maier, Klaus (2019) FPGA based real-time implementation of Bivariate Empirical Mode Decomposition. Circuits, Systems, and Signal Processing, 38 (1). pp. 118-137. DOI https://doi.org/10.1007/s00034-018-0844-2
Malik, Qasim Waheed and ur Rehman, Naveed and Gull, Sikender and Ehsan, Shoaib and McDonald-Maier, Klaus (2019) FPGA based real-time implementation of Bivariate Empirical Mode Decomposition. Circuits, Systems, and Signal Processing, 38 (1). pp. 118-137. DOI https://doi.org/10.1007/s00034-018-0844-2
Abstract
A field programmable gate array (FPGA)-based parallel architecture for the real-time and online implementation of the bivariate extension of the empirical mode decomposition (EMD) algorithm is presented. Multivariate extensions of EMD have attracted significant attention in recent years owing to their scope in applications involving multichannel and multidimensional data processing, e.g. biomedical engineering, condition monitoring, image fusion. However, these algorithms are computationally expensive due to the empirical and data-driven nature of these methods. That has hindered the utilisation of EMD, and particularly its bivariate and multivariate extensions, in real-time applications. The proposed parallel architecture is aimed at bridging this gap through real-time computation of the bivariate EMD algorithm. The crux of the architecture is the simultaneous computation of multiple signal projections, locating their local extrema and finally the calculation of their associated complex-valued envelopes for the estimation of local mean. The architecture is implemented on a Xilinx Kintex 7 FPGA and offers significant computational improvements over the existing software-based sequential implementations of bivariate EMD.
Item Type: | Article |
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Uncontrolled Keywords: | Bivariate empirical mode decomposition; Field programmable gate array (FPGA); Signal decomposition; Time-frequency analysis |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 11 Jun 2018 10:24 |
Last Modified: | 30 Oct 2024 20:45 |
URI: | http://repository.essex.ac.uk/id/eprint/22186 |
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