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Factorization based blind identification and separation of nonstationary seizure signals

Makkiabadi, B, Makkiabadi, B and Sanei, S (2012) Factorization based blind identification and separation of nonstationary seizure signals AISP 2012 - 16th CSI International Symposium on Artificial Intelligence and Signal Processing. pp. 617-622.

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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. © 2012 IEEE.

Item Type: Article
Authors :
NameEmailORCID
Makkiabadi, BUNSPECIFIEDUNSPECIFIED
Makkiabadi, BUNSPECIFIEDUNSPECIFIED
Sanei, SUNSPECIFIEDUNSPECIFIED
Date : 2012
Identification Number : 10.1109/AISP.2012.6313819
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 14:14
Last Modified : 31 Oct 2017 14:55
URI: http://epubs.surrey.ac.uk/id/eprint/744110

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