Costa, PauloBarroso, JoãoFernandes, HugoHadjileontiadis, Leontios J2025-10-172025-10-172012-08-21Costa et al.: Using Peano–Hilbert space filling curves for fast bidimensional ensemble EMD realization. EURASIP Journal on Advances in Signal Processing 2012 2012:1811687-6180http://hdl.handle.net/10400.8/14307Empirical mode decomposition (EMD) is a fully unsupervised and data-driven approach to the class of nonlinear and non-stationary signals. A new approach is proposed, namely PHEEMD, to image analysis by using Peano–Hilbert space filling curves to transform 2D data (image) into 1D data, followed by ensemble EMD (EEMD) analysis, i.e., a more robust realization of EMD based on white noise excitation. Tests’ results have shown that PHEEMD exhibits a substantially reduced computational cost compared to other 2D-EMD approaches, preserving, simultaneously, the information lying at the EMD domain; hence, new perspectives for its use in low computational power devices, like portable applications, are feasible.engEnsemble empirical mode decomposition (EEMD)Fast bidimensional EEMDPeano–Hilbert curvesjournal article10.1186/1687-6180-2012-181