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Adaptive fuzzy wavelet network control design for nonlinear systems
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Artificial wavelet neural network and its application in neuro-fuzzy models
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Nonlinear systems control using self-constructing wavelet networks
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Fuzzy wavelet neural network for prediction of electricity consumption
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New fuzzy wavelet neural networks for system identification and control
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Expert Systems with Applications: An International Journal
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Fuzzy Multiresolution Neural Networks
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A new approach to fuzzy wavelet system modeling
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Efficient reinforcement hybrid evolutionary learning for recurrent wavelet-based neuro-fuzzy systems
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
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Expert Systems with Applications: An International Journal
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Expert Systems with Applications: An International Journal
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ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
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FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
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Mathematical and Computer Modelling: An International Journal
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Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
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Inspired by the theory of multiresolution analysis (MRA) of wavelet transforms and fuzzy concepts, a fuzzy wavelet network (FWN) is proposed for approximating arbitrary nonlinear functions. The FWN consists of a set of fuzzy rules. Each rule corresponding to a sub-wavelet neural network (WNN) consists of single-scaling wavelets. Through efficient bases selection, the dimension of the approximated function does not cause the bottleneck for constructing FWN. Especially, by learning the translation parameters of the wavelets and adjusting the shape of membership functions, the model accuracy and the generalization capability of the FWN can be remarkably improved. Furthermore, an algorithm for constructing and training the fuzzy wavelet networks is proposed. Simulation examples are also given to illustrate the effectiveness of the method