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1)  discrete process neural network
离散过程神经元网络
2)  process neural networks
过程神经元网络
1.
A process neural networks model and its application to dynamic forecasting;
一种过程神经元网络模型及其在动态预测中的应用
2.
Process neural networks with time-varying inputs and outputs and learning algorithm;
一种时变输入输出过程神经元网络及学习算法研究
3.
Aimed at the problems of the time-varying information processing and the dynamic system modeling, two kinds of process neural network models,including the rational formula process neural networks and the process neural networks with time-varying inputs and outputs function,were built in this paper.
针对时变信息处理和动态系统建模等类问题,建立了输入输出均为时变函数的过程神经元网络和有理式过程神经元网络2种网络模型。
3)  process neural network
过程神经元网络
1.
Research and application of process neural network with two hidden-layer based on expansion of basis function;
基于基函数展开的双隐层过程神经元网络及其应用
2.
A dynamic prediction method based on process neural networks is proposed for the process forecasting and prediction problem of dynamic system.
针对动态系统过程预测预报问题,提出了一种基于过程神经元网络的动态预测方法。
3.
A modular process neural network model based on multi-basis-functions is brought forward in this article,in which the spatial aggregation and temporal limited accumulation of discrete-time inputs are involved.
提出一类基于多种正交基函数的模块化过程神经元网络模型,它融入了多时变输入的空间聚合和作用域限制的时间累积,并采用多种正交基函数在较小网络规模的条件下保证系统各种输入输出的精度,应用混合隐含层综合考虑了系统多类型输入对系统的作用,并应用模块化级联的方式在一定程度上减小了网络的总体容量,从而提高了整个网络的学习速度。
4)  Scattered neuronal network
离散型神经元网络
5)  Fuzzy process neural network
模糊过程神经元网络
6)  multi-aggregation process neural networks
多聚合过程神经元网络
1.
Aimed at the information process problem that the system inputs are multivariate process functions and multi-dimension process signals, this paper proposes a kind of the multi-aggregation process neuron and the multi-aggregation process neural networks model.
针对系统输入为多元过程函数以及多维过程信号的信息处理问题,提出了多聚合过程神经元和多聚合过程神经元网络模型。
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