SISO Nonlinear System Identification Using a Fuzzy-Neural Hybrid System

@article{Lin1997SISONS,
  title={SISO Nonlinear System Identification Using a Fuzzy-Neural Hybrid System},
  author={Cheng-Jian Lin},
  journal={International journal of neural systems},
  year={1997},
  volume={8 3},
  pages={
          325-37
        }
}
This paper describes a fuzzy-neural hybrid system for the identification of nonlinear dynamic systems with unknown parameters. The proposed model takes the form of a context-sensitive module in which a fuzzy system is used as a function module and a multilayer neural network is used as a context module. Fuzzy-neural hybrid systems with a decomposed structure reduce complexity and thus accelerate the learning process. Also, the parameters of a fuzzy system have clear physical meanings, which… CONTINUE READING

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