Support Vector-Enhanced Design of a T2FL Approach to Motor Imagery-Related EEG Pattern Recognition

The significance of the initialization procedure in the development of Type-2 fuzzy logic (T2FL) system-based classifiers should be highlighted considering their intrinsically non-linear nature. Initial structure identification has been recognized as a crucial stage in the design of an interval T2FL...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2007 IEEE International Fuzzy Systems Conference s. 1 - 6
Hlavní autori: Herman, P., Prasad, G., McGinnity, T.M.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.06.2007
Predmet:
Brain computer interfaces
Computer interfaces
Design methodology
Electrodes
Electroencephalography
Fuzzy logic
Impedance
Pattern recognition
Robustness
Uncertainty
ISBN:1424412099, 9781424412099
ISSN:1098-7584
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:The significance of the initialization procedure in the development of Type-2 fuzzy logic (T2FL) system-based classifiers should be highlighted considering their intrinsically non-linear nature. Initial structure identification has been recognized as a crucial stage in the design of an interval T2FL (IT2FL) classifier utilized in the framework of electroencephalogram (EEG)-based brain -computer interface (BCI). In conjunction with an efficient gradient-based learning algorithm it has allowed for robust exploitation of T2FL's capabilities to effectively handle uncertainties inherently associated with changing dynamics of electrical brain activity. This paper builds on the previous experiences in tackling the problem of inter-session classification of motor imagery (MI)-related EEG patterns. The major contribution of this work is an empirical investigation of the concept of support vector (SV) learning applied to structure identification of the IT2FL classifier. The SV-enhanced initialization scheme is found to compare favorably to both an arbitrary initialization and the clustering approach utilized in the preceding work in terms of the inter-session BCI classification performance of the fully trained IT2FLS evaluated on three subjects.
ISBN:1424412099
9781424412099
ISSN:1098-7584
DOI:10.1109/FUZZY.2007.4295661