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Rule-Base Parameter Optimization for a Multi-Stroke Fuzzy-Based Character Recognizer

In this paper the results of rule-base construction parameter optimization for a multi-stroke fuzzy character recognizer are compared. The experiment covers the investigation of the optimal number of samples used to build the rule-base and the parameter of the method to generate fuzzy sets from the training set collected from subjects. The various settings are evaluated with validation samples from the same group of test subjects.