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GA optimisation of Non-Singleton Fuzzy Logic System for ECG classification

This paper studies the ability of a non-singleton fuzzy logic system (NSFLS) that is evolved using Genetic Algorithm (GA) to handle the uncertainties in pattern classification problems. The performance of non-singleton and singleton systems for cardiac arrhythmias classification is compared. Results show that NSFLS can deal with uncertainty within its framework more efficiently, thereby enabling classification to be performed using features that are easier to extract.