A class of process neural network model with two hidden-layer based on expansion of basis function is brought forward.

提出一类基于基函数展开的双隐层过程神经元网络模型。

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In order to model and simulate systems with time-varying functions or processes, a feedback process neural network model with time-varying input and output functions is proposed.

针对输入和输出均为时变函数或过程的实际系统建模和仿真问题，提出一种输入和输出均为时变函数的反馈过程神经网络模型。

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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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