Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition

TLDR: Fuzzy rules and defuzzification: rules based on experience learning from examples decision tree approach neural network approach minimization of fuzzy rulesdefuzzification and optimization applications concluding remarks.

Abstract: Introduction: Fuzzy sets probability and fuzziness fuzzy models Membership functions: heuristic selections clustering approaches adjustment and toning applications concluding remarks Fuzzy clustering: clustering and fuzzy partition fuzzy c-means algorithm fuzzy cohonen clustering networks cluster validity and optimal fuzzy clustering applications concluding remarks Fuzzy rules and defuzzification: rules based on experience learning from examples decision tree approach neural network approach minimization of fuzzy rules defuzzification and optimization applications concluding remarks Fuzzy classifiers: fuzzy nearest neighbour classifier fuzzy multilayer perceptron fuzy decision trees fuzzy string matching applications concluding remarks Combined clasifications: introduction voting schemes maximum poteriori probability Dempster-Shafer evidence theory trained perceptron neural networks applications concluding remarks