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A neuro-fuzzy system for isolated hand-written digit recognition using a similarity fuzzy measure is presented. The system is composed of two main blocks: a first block that normalizes the input and compares it with a set of fuzzy patterns, and a second block with a multilayer perceptron to perform a neuronal classification. The comparison with the fuzzy patterns is performed via a fuzzy similarity measure that uses the Yager parametric t-norms and t-conorms. Along this work, several values of the...
A fuzzy method for the text error correction problem is introduced. The method is able to handle insert, delete and substitution errors. Moreover, it uses the measurement level output that an Isolated Character Classifier can provide. The method is based on a Deformed System, in particular, a deformed fuzzy automaton is defined to model the possible errors in the words of the texts. Experimental results show good performance in correcting the three types of errors.
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