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1·Diagonal recurrent neural network (DRNN) is a non-unity feedback network.

对角神经网络(DRNN)为非全反馈式动态神经网络。

2·The recurrent neural network model based on projective operator is studied.

研究了一种基于投影算子的神经网络模型。

3·The recurrent neural network(RNN) model based on projective operator is studied.

研究了一种基于投影算子的神经网络模型。

4·A locally recurrent neural network controller based on neural network is proposed.

基于人工神经网络提出了一种局部递归神经网络控制器。

5·This provides a new way to the fast training of complex valued recurrent neural network.

这为快速训练复值递归神经网络提供了一条新的途径。

6·A dynamic recurrent neural network to freeway macroscopic traffic flow modeling is presented.

提出用动态回归神经网络建立高速公路宏观交通流模型。

7·A structure and training algorithm for quasi-diagonal recurrent neural network (QDRNN) is presented.

提出一种准对角递归神经网络(QDRNN)结构及学习算法。

8·This is written about me on the diagonal recurrent neural network procedures, may be helpful to you.

这是我写的关于对角递归神经网络的程序，或许对你有所帮助。

9·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特性。

10·The dynamic recurrent neural network is analyzed, and how to use it for system identification is also analyzed.

对所提出的动态递归神经网络进行了分析，以及如何利用它们来进行系统辨识。