A Novel Dynamic Neural Network Structure for Nonlinear System Identification
نویسندگان
چکیده
Dynamic neural networks are often used for nonlinear system identification. This paper presents a novel series-parallel dynamic neural network structure which is suitable for nonlinear system identification. A theoretical proof is given showing that this type of dynamic neural network is able to approximate finite trajectories of nonlinear dynamical systems. Also, this neural network is trained to identify a practical nonlinear 3D crane system. Copyright c ©2005 IFAC.
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