Detection of multiple sclerosis with visual evoked potentials - an unsupervised computational intelligence system.

This paper describes the application of a novel unsupervised pattern recognition system to the classification of the visual evoked potentials (VEPs) of normal and multiple sclerosis (MS) patients. The method combines a traditional statistical feature extractor with a fuzzy clustering method, all imp...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:	IEEE Transactions on information technology in biomedicine 4, 3 (2000).
1. Verfasser:	Dasey, T.J
Format:	Artikel
Sprache:	English
Schlagworte:	ALOPEX. Karhunen-Loeve expansion vectors. Classification. Feature extraction. Fuzzy c-means. Fuzzy clustering method. Minimization. Multiple sclerosis. Objective error function. Optimization routine. Parallel neural network architecture. Statistical feature extractor. Unsupervised computational intelligence system. Unsupervised pattern recognition system. Visual evoked potentials.