System Identification and Adaptive Filter Using a Novel Fuzzy Neuro System
نویسندگان
چکیده
This paper proposes a new intelligent scheme using type-2 fuzzy inference system in neural network structure. This type-2 fuzzy neural network system (type-2 FNN) combines the advantages of type-2 fuzzy logic systems (FLSs) and neural networks (NNs). The general FNN system (called type-1 FNN system) has the properties of parallel computation scheme, easy to implement, fuzzy logic inference system, and parameters convergence. For considering the fuzzy rules uncertainties, we use the type-2 FLSs to develop a type-2 FNN system. In this paper, the previous results of type-1 FNN systems are extended to a type-2 one. Furthermore, the corresponding learning algorithm is derived by back-program algorithm with time-varying learning rate to obtain high-speed convergence. Nonlinear system identification and neuro-fuzzy adaptive filter for nonlinear channel equalization are presented to illustrate the effectiveness of our approach. Copyright c © 2007 Yang’s Scientific Research Institute, LLC. All rights reserved.
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