In this model, the continuous input-output mapping of the system is realized by nonlinear mapping capability to the time variable of process neural networks.

该模型利用过程神经元网络所具有的对时间变量的非线性映射能力，实现系统的输入、输出之间的连续映射关系。

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For the problem that the input and output of real systems is a continuous process relative to time, this paper proposed a process neural network model for continuous function approximation.

针对实际系统的输入输出是与时间有关的连续过程，提出了一类用于连续过程逼近的过程神经元网络模型。

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For the problem that the input and output of real systems is a continuous process relative to time, this paper proposed a process neural network model for continuous function approximation.

针对实际系统的输入输出是与时间有关的连续过程，提出了一类用于连续过程逼近的过程神经元网络模型。

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