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Feature selection via orthogonal expansion of MEG signals

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4 Author(s)
Angelidou, A. ; Dept. of Electr. Eng., Aristotelian Univ. of Thessaloniki, Greece ; Strintzis, M.G. ; Panas, S. ; Anogianakis, G.

The processing of magnetoencephalogram (MEG) signals via orthogonal expansion is examined. The Karhunen-Loeve expansion is used as a tool for feature selection in order to lower the dimensionality of the data and achieve data compression. Data reduction achieved through this method is approximately 6:1. A comparison with the data reduction achieved via autoregressive modeling is made, and the advantages and disadvantages of the Karhunen-Loeve method are discussed

Published in:

Electrotechnical Conference, 1991. Proceedings., 6th Mediterranean

Date of Conference:

22-24 May 1991

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