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MEG-Base Visual Brain Decoding: A New Approach Feature Extraction in the Mind Reading Patterns Classification
ISSN: en
Publisher: author
MEG-Base Visual Brain Decoding: A New Approach Feature Extraction in the Mind Reading Patterns Classification
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Abstract
This paper presents a new feature extraction approach for improvement of brain decoding by increasing classification performance. For this purpose, different combinations of nine features are assumed, and their classification performances have been compared with together. Then, the best combination is located in one vector with different weights. This vector can enhance the classification performance. Five kinds of clip are shown to a person in two days as stimuli while the MEG signal of his head surface is recorded. The recorded signals classification shows that the type of clips characterized by a measurement as one second length signal with high accuracy. Therefore, the classification accuracy in MEG data can be changed using a proper features, number of features, and the weight of each feature selection. Index Terms— Magneto encephalography, classification, feature extraction, brain decoding
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International Category Code (ICC):
ICC-0202
Mohammad Reza Daliri, Mohsen Parto Dezfoli, Mohammad Ali Partodezfoli..
International Article Address (IAA):
IAA.ZONE/en8263en
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