A genetic interval type-2 fuzzy logic-based approach for generating interpretable linguistic models for the brain P300 phenomena recorded via brain–computer interfaces-Reference-Cited by-同舟云学术

A genetic interval type-2 fuzzy logic-based approach for generating interpretable linguistic models for the brain P300 phenomena recorded via brain–computer interfaces

Published:2014-05-18 Issue:4 Volume:19 Page:1019-1035
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Alhaddad Mohammed J.,Mohammed Ahmed,Kamel Mahmoud,Hagras Hani

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-014-1312-y.pdf

Reference23 articles.

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3. Citi L, Poli R, Caterina C (2009) Exploiting P300 amplitude variations can improve classification accuracy in Donchin’s BCI Speller. In: Proceedings of the 4th International IEEE EMBS conference on neural engineering, Antalya, pp 478–481

4. Croux C, Filzmoser P, Joossens K (2008) Classification efficiencies for robust linear discriminant analysis. Stat Sinica 18(2):581–599

5. Herman P, Prasad G, Mcginnity T (2008) Designing a robust type-2 fuzzy logic classifier for non-stationary systems with application in brain-computer interfacing. In: Proceedings of the 2008 IEEE international conference on systems. Man and cybernetics, Singapore, pp 1343–1349

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