Using Peano–Hilbert space filling curves for fast bidimensional ensemble EMD realization

Costa, Paulo; Barroso, João; Fernandes, Hugo; Hadjileontiadis, Leontios J

http://hdl.handle.net/10400.8/14307

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
1687-6180-2012-181.pdf		1.73 MB	Adobe PDF	Download

Send Feedback

Authors

Costa, Paulo

Barroso, João

Fernandes, Hugo

Hadjileontiadis, Leontios J

Abstract(s)

Empirical 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.

Keywords

Ensemble empirical mode decomposition (EEMD) Fast bidimensional EEMD Peano–Hilbert curves

URI

http://hdl.handle.net/10400.8/14307

Citation

Costa et al.: Using Peano–Hilbert space filling curves for fast bidimensional ensemble EMD realization. EURASIP Journal on Advances in Signal Processing 2012 2012:181