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A new method for design of a classification system using the feature extraction and evolutionary programming (EP) are discussed. In this paper, a neuro-fuzzy classification model (NFCM) is proposed. The optimal fuzzy membership functions of the NFCM are extracted from the training data using EP. The NFCM contains the feature extraction unit and the inference unit. In order to improve the proposed...
In this study, a robust algorithm with a fuzzy sliding model controller (FSMC) is used to synchronization of a Duffing-Holmes system. The robust algorithm is an output factor of the fuzzy sliding model controller. The control rules of FSMC are based on the Lyapunov stability theorem. The objective of synchronization is to study a master-and-slave system to be synchronized with both uncertainties and...
The problem of the data analysis and the pattern recognition, searching the relationship between the feature variables of a database and inferred results are special important. In this paper, a fuzzy classification model is established to solve the classification problem. And the objective is to propose an adaptive classification system that can be generating the fuzzy IF-THEN rules automatically...
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