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- W18125859 abstract "Publisher Summary This chapter discusses several applications of neurofuzzy technology and their modeling. By mapping the fuzzy pattern classification process into a connectionist framework, various connectionist fuzzy classifiers for the problems of pattern recognition can be achieved. The first fuzzy neural network model presented in this chapter is based on a four-layer feedforward neural network structure for implementing a “weighted Euclidean distance” fuzzy classification procedure. They apply one-pass learning algorithms. The connectionist fuzzy classifier (CFC) model and its variations have been adopted for the problems of speech recognition, color image recognition, and information retrieval on the Internet. The purpose of developing this model is to combine the advantages of the back-propagation and PNN models. The second model presented in this chapter is for the applications of fuzzy expert systems and control engineering. The chapter presents NNFI and its reinforcement-learning version, the RFNN-DPS model. These are constructed with a three-layered network structure and consist of a few kinds of neurons: linguistic neurons, rule neurons, and credit-based exploration neurons. Finally, the chapter presents a third kind of application: function approximation and color space mapping. The presented fuzzy CMAC model can be successfully used in general function approximation and color reproduction." @default.
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- W18125859 title "Implementation Techniques and Applications of Fuzzy Neural Network Systems" @default.
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