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IEEE/ICACT20260121 Slide.07        [Big Slide]	Oral Presentation
	Advantage of this technique: Highly efficient for non-stationary data (e.g., EEG, seismic, financial), as it does not require stationarity or linearity assumptions. Mode Mixing Problem: A major limitation where a single IMF contains signals of widely disparate scales, or similar oscillations appear in different IMFs. EEMD (Ensemble EMD): A technique that adds white noise to the signal to mitigate mode mixing by forcing the algorithm to explore different scales. Applications: Commonly used in biomedical signal processing, seismic signal analysis, and financial data analysis.

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