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In this paper, first an enhanced NeuroFuzzy method for modeling nonlinear system is presented. In this method we use EM algorithm for identification of local models, which gain us model mismatch covariance. The achieved model can be stated in state space model as a linear time-varying system. As the noise and model mismatch covariace is known, Kalman filter can be easily used for estimation fusion...
In this paper, first an enhanced neuro-fuzzy method for modeling nonlinear system is presented In this method we use EM algorithm for identification of local models, which gain us model mismatch covariance. The achieved model can be stated in state space model as a linear time-varying system. As the noise and model mismatch covariance is known, Kalman filter can be easily used for centralized estimation...
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