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dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorSompong Dhompongsaen_US
dc.description.abstractWe have developed a linguistic perceptron (LP) to deal with the problem in pattern recognition where inputs are uncertain. This algorithm is based on the extension principle and the decomposition theorem. Several synthetic data sets are used to illustrate the behavior of this linguistic perceptron in linearly separable, nonlinearly separable and nonseparable situations. We also compare the results from the linguistic perceptron with that from the regular perceptron. © 2006 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titleAn investigation of a linguistic perceptron in a nonlinear decision boundary problemen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleIEEE International Conference on Fuzzy Systemsen_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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