Automatic Generation of a Fuzzy Rule Base for Online Handwriting Recognition
نویسندگان
چکیده
An automatic method to generate fuzzy rules and their membership functions to recognize handwritten characters is described. Firstly an initial rule base is created on the basis of a referential data set containing handwriting prototypes. Subsequently the classification behavior of the fuzzy rules is optimized with a genetic algorithm, which is regarded as a typical solution to NP-complete problems. A suitable fitness function which corresponds to the human perception of the linguistic variables is obtained. The proposed rule generation process extends the learning and adaptive capabilities of existing fuzzy rule based recognition system.
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