A New Approach to Empirical Mode Decomposition Based on Akima Spline Interpolation Technique

The objective of this research work is to extend the scope of the empirical mode decomposition (EMD) algorithm, as an efficient tool to decompose the nonlinear and non-stationary time series. For EMD to be widely applicable, the extension utilizes both clean and noisy data sets. When constructing up...

詳細記述

書誌詳細

主要な著者:	Muhammad Ali, Dost Muhammad Khan, Imran Saeed, Huda M. Alshanbari
フォーマット:	Artigo
言語:	Inglês
出版事項:	IEEE 2023-01-01
シリーズ:	IEEE Access
主題:	Akima empirical mode decomposition (EMD) fast Fourier transform (FFT) intrinsic mode functions (IMFs) variational mode decomposition (VMD) complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN)
オンライン･アクセス:	https://ieeexplore.ieee.org/document/10061218/
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