Please use this identifier to cite or link to this item: https://doi.org/10.1109/CEC.2007.4424675
Title: GA optimisation of non-singleton fuzzy logic system for ECG classification
Authors: Chua, T.W.
Tan, W.W. 
Issue Date: 2007
Source: Chua, T.W.,Tan, W.W. (2007). GA optimisation of non-singleton fuzzy logic system for ECG classification. 2007 IEEE Congress on Evolutionary Computation, CEC 2007 : 1677-1684. ScholarBank@NUS Repository. https://doi.org/10.1109/CEC.2007.4424675
Abstract: 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. ©2007 IEEE.
Source Title: 2007 IEEE Congress on Evolutionary Computation, CEC 2007
URI: http://scholarbank.nus.edu.sg/handle/10635/70407
ISBN: 1424413400
DOI: 10.1109/CEC.2007.4424675
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