Improved Common Spatial Patterns on EEG Feature Extraction

Yu Yu Gao

doi:10.4028/www.scientific.net/AMR.926-930.1814

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 926-930Improved Common Spatial Patterns on EEG Feature...

Improved Common Spatial Patterns on EEG Feature Extraction

Abstract:

For extracting relatively stable and invariable feature from non-stationary EEG in mult-class pattern, many scholars study a feature extraction method, which is called as modified multi-classcommon spatial pattern. It adopts one-to-one strategy to expand common spatial pattern to multi-class classification. While for the solution of airspace filter, Kullback-Leibler distance defines pattern of discrimination of minimize difference within class and maximize difference between classes. And it establishes a function to measure difference within the class. The experiment verifies that the algorithm can obtain feature information with recognition capability which implys in the non-stationary EEG and acquires preferable classification result.

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Periodical:

Advanced Materials Research (Volumes 926-930)

Pages:

1814-1817

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.926-930.1814

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Online since:

May 2014

Authors:

Yu Yu Gao

Keywords:

Common Spatial Patterns, Difference within Class, EEG, Feature Extraction, Kullback-Leibler Distance

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