A New Method for Complexity Reduction of Neuro-fuzzy Systems with Application to Differential Stroke Diagnosis

Authors:
Krzysztof Cpałka;Olga Rebrova;Leszek Rutkowski
Affiliations:
Department of Computer Engineering, Czestochowa University of Technology, Poland and Department of Artificial Intelligence, Academy of Humanities and Economics in Łódź, Poland;Institute of Neurology, Russian Academy of Medical Sciences, Russia;Department of Computer Engineering, Czestochowa University of Technology, Poland and Department of Artificial Intelligence, Academy of Humanities and Economics in Łódź, Poland
Venue:
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Year:
2009

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Abstract

In the paper we propose a new method for designing and reduction of neuro-fuzzy systems for stroke diagnosis. The concept of the weighted parameterized triangular norms is applied and neuro-fuzzy systems based on fuzzy S-implications are derived. In subsequent stages we reduce the linguistic model. The results are implemented to solve the problem of stroke diagnosis.