A design algorithm of membership functions for a fuzzy neuron using example-based learning

The authors describe a design algorithm for extraction of membership functions of a fuzzy neuron based on example-based learning with optimization of cross-detecting lines. This algorithm facilitates design without the knowledge of experts. The algorithm was verified by recognition of hand-written characters. Using this algorithm, a fuzzy neuron can be designed very easily without knowledge about the features of the character, and optimum membership functions can be extracted.<
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