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Neural networks for identification of nonlinear systems under random piecewise polynomial disturbances

机译:随机分段多项式扰动下的非线性系统辨识神经网络

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摘要

The problem of identification of a nonlinear dynamic system is considered. A two-layer neural network is used for the solution of the problem. Systems disturbed with unmeasurable noise are considered, although it is known that the disturbance is a random piecewise polynomial process. Absorption polynomials and nonquadratic loss functions are used to reduce the effect of this disturbance on the estimates of the optimal memory of the neural-network model.
机译:考虑了非线性动力学系统的辨识问题。两层神经网络用于解决问题。尽管已知干扰是一个随机的分段多项式过程,但仍考虑了受到无法测量的噪声干扰的系统。使用吸收多项式和非二次损失函数来减少这种干扰对神经网络模型的最佳记忆估计的影响。

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