Mehmet Dogan Elbi

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Empirical mode decomposition (EMD) is a tool developed for analyzing nonlinear and nonstationary signals. It is capable of splitting any signal into a set of oscillation modes known as intrinsic mode functions and a residual function. Although the EMD satisfies the perfect signal reconstruction property by superimposing all the oscillation modes, it is not(More)
The reconstruction problem of a high-resolution (HR) signal from a set of its noise-corrupted low-resolution (LR) versions is considered. As a part of this problem, a hybrid method that consists of four operation units is proposed. The first unit applies noise reduction based on the empirical mode decomposition interval-thresholding to the noisy LR(More)
The empirical mode decomposition (EMD) is a popular tool that is valid for nonlinear and nonstationary signal analysis. Applying this tool to any given signal reveals a finite set of oscillatory modes termed intrinsic mode functions (IMFs) and a residual. The sum of all extracted IMFs and the residual reconstructs the original signal without any information(More)
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