Volume 29 Issue 3
Mar.  2003
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Chen Ping, Qiu Lihua, Wang Zhanlinet al. Modeling of Nonlinear System with Diagonal Recurrent Neural Network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2003, 29(3): 248-251. (in Chinese)
Citation: Chen Ping, Qiu Lihua, Wang Zhanlinet al. Modeling of Nonlinear System with Diagonal Recurrent Neural Network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2003, 29(3): 248-251. (in Chinese)

Modeling of Nonlinear System with Diagonal Recurrent Neural Network

  • Received Date: 10 Oct 2001
  • Publish Date: 31 Mar 2003
  • Based on an analysis on the modeling principles of nonlinear system, the identification of a nonlinear system was realized with Diagonal Recurrent Neural Networks (DRNN). Serial-parallel identification architecture was applied in the modeling. Time variation was taken into account in the adjustment algorithm of weights. Compared with static neural network, the method based on DRNN displays better ability to deal with a dynamic system, due to its advantages such as without the need of system order number, a smaller neural network structure and a faster convergence. Simulation results testified the feasibility and validity of the proposed method.

     

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