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Research on nonlinear system identification based on input linearization dynamic recurrent neural network

机译:基于输入线性化动态递归神经网络的非线性系统辨识研究

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In this paper, it studies the problems of the on-line identification on the nonlinear and time-lag SISO dynamic system. It puts forward the recurrent structure to linearize the input neurons of the neural network which can describe the feasibility of the algorithm, so the neural network has the dynamic on-line identification capability. Simulation results show that the input linearization dynamic recurrent network has a strong self-adaptability and robustness. It gives a new method for SISO nonlinear dynamic system identification.
机译:本文研究了非线性和时滞SISO动态系统的在线辨识问题。提出了递归结构来线性化神经网络的输入神经元,可以描述该算法的可行性,从而使神经网络具有动态的在线识别能力。仿真结果表明,输入线性化动态递归网络具有很强的自适应性和鲁棒性。为SISO非线性动态系统辨识提供了一种新方法。

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