 Multidimensional empirical mode decomposition

Multidimensional Empirical Mode Decomposition (MEMD) is an advanced signal processing technique, an extension of the traditional Empirical Mode Decomposition (EMD) used primarily for analyzing one-dimensional signals. EMD is a method designed to decompose a signal into a set of intrinsic mode functions (IMFs) that better capture its oscillatory modes, enabling more effective analysis, filtering, and interpretation of complex signals.