Abstract
Empirical mode decomposition (EMD) offers a data-driven approach for signal filtering. In this letter, a new de-noising scheme is proposed, which estimates a pertinent probability distribution parameter with the Newton-Raphson root-finding method. The parameter estimation reduces the computational cost of relevant mode selection by reducing the range of possible mode distribution shapes. Computational complexity is assessed, revealing significant reduction in the number of operations required in comparison to a previous de-noising scheme which utilized the same form of statistical filtering. Furthermore, simulation results of the proposed EMD filter show superior performance over other EMD de-noising techniques with real biomedical recordings corrupted by colored noise.
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