This paper investigates the problem of the model validation in identifying discrete-time-nonlinear dynamic systems by using neural networks with a single hidden layer.

讨论了利用仅含一个隐层的前馈多层神经网络来辨识离散时间非线性动态系统时的模型检验问题。

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With the best polynomial approximation as a metric, the rate of approximation of the neural networks with single hidden layer to a continuous function is estimated by using a constructive approach.

以最佳多项式逼近为度量，用构造性方法估计单隐层神经网络逼近连续函数的速度。

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With the best polynomial approximation as a metric, the rate of approximation of the neural networks with single hidden layer to a continuous function is estimated by using a constructive approach.

以最佳多项式逼近为度量，用构造性方法估计单隐层神经网络逼近连续函数的速度。

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