A ROBUST AND PRACTICAL METHOD TO SEPARATE PERIODIC SIGNALS FROM MEG DATA USING SECOND ORDER STATISTICS

Hidekazu Fukai

Abstract

The analyses of recordings of magnetoencephalography (MEG) and other imaging techniques may require the separation of periodic signals from the observed signals. Blind source separation (BSS) is widely used for the separation of specific signals these days. Though several algorithms based on the BSS scheme for the separation of periodic signals have been proposed, they usually assume the system to be well-posed, satisfactory results often cannot be obtained for practical recordings. In this study, we show that a method based on the joint approximate diagonalization of correlation matrices with several time delays (JADCM) is robust and good results can be obtained by choosing the time delays carefully, especially in practical ill-posed situations such as signal separation from MEG recordings. The performance of the proposed method is compared with that of Periodic BSS and JADCM using the conventional parameter set.

References

  1. Barros, A. and Cichocki, A. (2001). Extraction of specific signals with temporal structure. Neural Computation, 13:1995-2003.
  2. Ziehe, A. and Müller, K. (1998). Tdsep-and efficient algorithm for blind separation using time structure. In Proc. Int. Conf. on Artificial Neural Networks (ICANN'98), pages 675-680.
  3. Ziehe, A., Müller, K., Nolte, G., Mackert, B., and Curio, G. (2000). Artifact reduction in magnetoneurography based on time-delayed second-order correlations. IEEE Trans. Biomed. Eng., 47:75-87.
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Paper Citation


in Harvard Style

Fukai H. (2011). A ROBUST AND PRACTICAL METHOD TO SEPARATE PERIODIC SIGNALS FROM MEG DATA USING SECOND ORDER STATISTICS . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011) ISBN 978-989-8425-35-5, pages 372-377. DOI: 10.5220/0003296103720377


in Bibtex Style

@conference{biosignals11,
author={Hidekazu Fukai},
title={A ROBUST AND PRACTICAL METHOD TO SEPARATE PERIODIC SIGNALS FROM MEG DATA USING SECOND ORDER STATISTICS},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)},
year={2011},
pages={372-377},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003296103720377},
isbn={978-989-8425-35-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)
TI - A ROBUST AND PRACTICAL METHOD TO SEPARATE PERIODIC SIGNALS FROM MEG DATA USING SECOND ORDER STATISTICS
SN - 978-989-8425-35-5
AU - Fukai H.
PY - 2011
SP - 372
EP - 377
DO - 10.5220/0003296103720377