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2014 | OriginalPaper | Chapter

Decoding the Long Term Memory Using Weighted Thresholding Union Subspaces Based Classification on Magnetoencephalogram

Authors : Sahar Tavakoli, Emad Fatemizadeh

Published in: Artificial Intelligence and Signal Processing

Publisher: Springer International Publishing

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Abstract

In this paper Long Term Memory (LTM) process during leftward and rightward orientation recalling have been analyzed using Magnetoencephalogram (MEG) signals. This paper presents a novel criterion for decision making using union subspace based classifier. The proposed method involves the Eigenvalues from Singular Value Decomposition (SVD) of each subspace not only to select basis for each subspace but also to weight the decision making criterion to discriminate two classes. The proposed method has provided orientation detection from recalling signal with 6.75 percent increase in classification accuracy compared to better results on this data.

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Title: Decoding the Long Term Memory Using Weighted Thresholding Union Subspaces Based Classification on Magnetoencephalogram
Authors: Sahar Tavakoli
Emad Fatemizadeh
Publisher: Springer International Publishing
Book: Artificial Intelligence and Signal Processing
Print ISBN: 978-3-319-10848-3

Electronic ISBN: 978-3-319-10849-0

Copyright Year: 2014
DOI: https://doi.org/10.1007/978-3-319-10849-0_17

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