A virtual instrument for efficient blind-source separation of nonstationary signals (CROSBI ID 637908)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Milanović, Željka ; Saulig, Nicoletta ; Sučić, Viktor
engleski
A virtual instrument for efficient blind-source separation of nonstationary signals
In this paper two methods for blind source separation of nonstationary signals, such as electroencephalogram output, applied to time frequency distributions are compared through implementation in a virtual instrument. Both methods are based on image processing approaches, but adopt different strategies for solving the blind source separation problem: the first method is based on a data clustering extraction, while the second one relies on the initial estimation of number of components followed by an iterative peak detection and extraction algorithm. The proposed virtual instrument provides an efficient and fast method for medical signal analysis, with low execution time and low resource consumption.
Virtual Instrument; Time-frequency distributions; K-means clustering; local Renyi entropy; Image Segmentation
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Podaci o prilogu
2016.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the First International Multidisciplinary Conference on Computer and Energy Science (SpliTech2016)
Podaci o skupu
International Multidisciplinary Conference on Computer and Energy Science (Splitech2016)
poster
13.07.2016-15.07.2016
Split, Hrvatska