A CNN based system to blind sources separation of MEG signals

Author

Bucolo, M. ; Fortuna, Luigi ; Frasca, Mattia ; La Rosa, Massimo

Author_Institution

Dipt. Elettrico, Elettronico e Sistemistico, Universita degli Studi di Catania

fYear

2002

fDate

22-24 Jul 2002

Firstpage

195

Lastpage

201

Abstract

In this paper a cellular neural network (CNN) based system to perform a real-time, parallel processing of magetoencephalographic data is proposed. In particular, a nonlinear approach to blind sources separation, instead of the linear procedure performed by independent component analysis, is introduced. Moreover, the characteristic spatial distribution of the cells in the CNN system has been exploited to reproduce the topology of the acquisition channels over the scalp.

Keywords

blind source separation; cellular neural nets; magnetoencephalography; medical diagnostic computing; medical signal processing; parallel processing; real-time systems; CNN based system; MEG signals; acquisition channel topology; blind sources separation; cellular neural network; magetoencephalography; real-time parallel processing; scalp; spatial distribution; Cellular neural networks; Electroencephalography; Heart beat; Hemodynamics; Humans; Independent component analysis; Magnetic separation; Real time systems; SQUIDs; Scalp;

fLanguage

English

Publisher

ieee

Conference_Titel

Cellular Neural Networks and Their Applications, 2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on

Print_ISBN

981-238-121-X

Type

conf

DOI

10.1109/CNNA.2002.1035053

Filename

1035053