DocumentCode :
3453881
Title :
Factorization based blind identification and separation of nonstationary seizure signals
Author :
Makkiabadi, Bahador ; Sanei, Saeid
Author_Institution :
Fac. of Eng. & Phys. Sci., Univ. of Surrey, Guildford, UK
fYear :
2012
fDate :
2-3 May 2012
Firstpage :
617
Lastpage :
622
Abstract :
In this paper, a new blind identification and source separation method, which explicitly uses nonstationarity of the sources in separation of their instantaneous mixtures, is developed and effectively used for separation of seizure signals. In this approach tensor factorization concept has been exploited for which the optimization steps require nonstationarity of the sources. Based on this method simultaneous blind separation and identification is achieved. The algorithm is applied to mixtures of synthetic nonstationary sources and for separation of seizure brain sources from natural EEG signals and the results are compared with those of some recently published methods.
Keywords :
blind source separation; electroencephalography; matrix decomposition; medical signal processing; optimisation; tensors; factorization based blind identification; instantaneous mixtures; natural EEG signals; nonstationary seizure signals; optimization steps; seizure brain sources; source separation method; synthetic nonstationary sources; tensor factorization concept; Argon; Blind Source Separation; Nonstationary; Seizure; Tensor Factorization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on
Conference_Location :
Shiraz, Fars
Print_ISBN :
978-1-4673-1478-7
Type :
conf
DOI :
10.1109/AISP.2012.6313819
Filename :
6313819
Link To Document :
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