辨识结果表明，动态递归网络模型优于传统辨识模型，适于非线性、不确定结构的辨识。
Results of identification show that the Elman's recurrent model is superior to the traditional model. It is adaptive to the identification of the non linear and uncertain structure.
无限区间上s -分布时滞广义递归神经网络模型概周期解的全局渐近稳定性。
Global asymptotic stability of general recurrent neural network models with S-type distributed delays on infinite intervals.
本文用递归神经网络逼近非线性ARMA模型预测电力短期负荷。
The recursive neural network based nonlinear approaching ARMA model is adopted for short-term power load prediction in this paper.
提出一种在用户-网络接口处利用对角递归神经网络(DRNN)作为自适应预测器，实现AT M网络自适应拥塞控制的模型。
This paper presents an adaptive congestion control model in ATM networks at the user to network interface by using a diagonal recurrent neural network (DRNN) as an predictor.
由于其反馈特征，使得递归神经网络模型能获取系统的动态响应特性。
With the feedback behavior, the recurrent neural network can catch up with the dynamic response of the system.
由于其反馈特征，使得递归神经网络模型能获取系统的动态响应。
With the feedback behavior, the recursive neural network can catch up with the dynamic response of the system.
本文利用递归神经网络来建立异步电机转速辩识模型，其网络学习采用实时递归学习算法。
This paper presents a model for identifying induction motor speed using the recurrent neural network, which is trained by a real time recurrent learning algorithm.
立方形递归网络是一类具有良好拓扑性质的互连网络模型。
Cubelike recursive networks are novel sorts of interconnection networks that have some attractive topological properties and good parameters.
这个过程被递归地使用一次或两次，然后将结果归并到全局网络模型中。
This process is applied recursively for one or two levels, and the result merged into the global network model.
应用该模型对线性结构和非线性结构在变阻尼控制和外荷载激励下结构的响应进行了数值仿真，表明所提的动态递归神经网络可以达到较高的预测精度。
Simulations on linear and nonlinear structures demonstrate that RDRNN is very effective on predicting the response of a structure subject to semi-active control and external excitation.
针对板带轧机液压agc系统在线故障诊断问题，建立了一种基于非线性自回归滑动平均模型NARMA的递归神经网络，通过AIC定阶法确定模型阶次。
For on-line fault diagnosis of hydraulic AGC system on strip rolling mill, a recursive neural network model based on NARMA was established. The model order is determined by AIC method.
应用实例验证了所提出的递归神经网络预测模型的有效性。
The presented prediction approach is proved to be useful and effective with simulation resu...
应用实例验证了所提出的递归神经网络预测模型的有效性。
The presented prediction approach is proved to be useful and effective with simulation resu...
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