1D Multivariate Empirical Mode Decomposition (MEMD) | Part 2

As the second part of a small series on the Multivariate Empirical Mode Decomposition (MEMD), this video provides a detailed overview about all steps involved in the MEMD algorithm. Each step is explained using exemplary data to gain a deeper and more intuitive understanding of the procedure. MEMD, Part 1:    • 1D Multivariate Empirical Mode Decompositi...   univariate EMD:    • Empirical Mode Decomposition (1D, univaria...   ---------------------------------------------------------------------------------------------------------------------------------------------------- References: Rehman, N., & Mandic, D. P. (2010). Multivariate empirical mode decomposition. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 466(2117), 1291-1302. https://doi.org/10.1098/rspa.2009.0502 Hemakom, A., Goverdovsky, V., Looney, D., & Mandic, D. P. (2016). Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain–computer interface applications. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), 20150199. https://doi.org/10.1098/rsta.2015.0199 Personal webpage of Prof. Mandic, where you can get the matlab code for MEMD and APIT-MEMD: https://www.commsp.ee.ic.ac.uk/~mandi... ---------------------------------------------------------------------------------------------------------------------------------------------------- Time schedule: 00:00 Introduction 01:48 The algorithm 09:22 The stopping criterion 16:32 The sifting