1. 北京大学信息科学技术学院,北京,100871
2. 大庆石油学院计算机与信息技术学院,黑龙江,大庆,163318
3. 北京大学信息科学技术学院北京,100871
4. 大庆石油学院计算机与信息技术学院黑龙江大庆,163318
纸质出版:2006
移动端阅览
许少华, 何新贵, 刘 坤, 等. 关于连续过程神经元网络的一些理论问题[J]. 电子学报, 2006,34(10):1838-1841.
XU Shao-hua, HE Xin-gui, LIU Kun, et al. Some Theoretical Issues on Continuous Process Neural Networks[J]. Acta Electronica Sinica, 2006, 34(10): 1838-1841.
针对输入/输出均为连续时间函数的非线性系统信号处理和建模问题
提出了一种连续过程神经元和过程神经元网络模型.连续过程神经元的输入/输出均为连续时间函数
其时空聚合运算能同时反映连续时变输入信号的空间聚合作用和输入过程中的时间累积效应
可实现输入/输出之间非线性实时或若干时间单元延迟的映射关系.文中给出了一种输入输出均为连续时间函数的前馈过程神经元网络模型
并证明了相应的连续性
函数逼近能力和计算能力等性质定理.
Aim at the problems that the inputs and outputs of some practical nonlinear systems are Continuous time signals
we brought forward a Continuous process neuron and process neural networks model.The input and output of the defined process neuron are Continuous time functions
and the space-time aggregation operation can reflect the space aggregation of the input signals and the time cumulative effect in the process of input at the same time
and can also realize the nonlinear real-time mapping between the input and output.A Continuous feedforward process neural networks model is given in this paper
and the corresponding property theorems are also proved
including continuity
function approximation ability and computational capacity.
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