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。
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。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed.
分析了动态递归神经网络系统辨识的参数学习算法。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed. D.
分析了动态递归神经网络系统辨识的参数学习算法。
A novel indirect adaptive controller based on dynamic recurrent fuzzy neural network (DRFNN) is proposed for affine nonlinear system.
针对仿射非线性系统，提出了一种新型的基于动态递归模糊神经网络(DRFNN)的间接自适应控制器。
Using dynamic recurrent neural networks as identification and controller, the minimum error control of robot tracking the idea locus is implemented.
采用动态对角回归神经网络作为辨识器和控制器，实现了机器人轨迹跟踪的最小误差控制。
Then, aiming at the existing problem, the algorithm of dynamic recurrent neural network, RBF neural network and adaptive inverse control is studied in the paper.
接着，结合其存在的问题，对动态递归神经网络、R BF神经网络和自适应逆控制进行了算法研究。
An adaptive PID control scheme based on dynamic recurrent neural network is presented. The control system is consisted of the neural network identifier and the neural network controller.
提出一种基于动态递归神经网络的自适应pid控制方案，该控制系统由神经网络辨识器和神经网络控制器组成。
This paper presents an adaptive PID control scheme based on dynamic recurrent neural network. The control system is consisted of the neural network identifier and the neural network controller.
提出一种基于动态递归神经网络的自适应pid控制方案，该控制系统由神经网络辨识器和神经网络控制器组成。
Since a static fuzzy neural network cannot deal with the temporal problem, a dynamic fuzzy neural network (DFNN) with recurrent units is proposed.
针对静态网络无法处理暂态问题，对具有递归环节的动态模糊神经网络进行了研究。
An adaptive gradient descent algorithm for training simplified internally recurrent networks (SIRN) is developed and a new method of reconciling nonlinear dynamic data based on SIRN is proposed.
研究了简化型内回归神经网络基于自适应梯度下降法的训练算法，并提出了一种基于简化型内回归神经网络的非线性动态数据校核新方法。
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。
Diagonal recurrent neural network (DRNN) is a modified model of the fully connected recurrent neural network with the advantage in capturing the dynamic behavior of a system.
对角循环神经网络是一类经过修正的全连接循环神经网络，在系统动态行为的俘获方面具有明显的优势。
An algorithm is proposed to solve the Nash equilibrium solution for ann-person noncooperative dynamic game by an annealing recurrent neural network for extremum seeking algorithm (ESA).
针对如何解算n人非合作的动态博弈对策中的纳什均衡解问题，提出一种利用退火回归神经网络极值搜索算法解算纳什均衡解的方法。
To order to reduce cluttered and textured elements, we present a method for suppressing texture edges via dynamic properties of recurrent inhibition in non-classical receptive field.
为了减少背景中的纹理边缘成分并突出区域的边界，本文利用非经典感受野循环抑制的动态属性提出了一种纹理抑制方法。
AIM: To explore the dynamic changing regularity of recurrent rate of unipolar depression.
目的：探索单相抑郁症复发率的动态变化规律。
AIM: To explore the dynamic changing regularity of recurrent rate of unipolar depression.
目的：探索单相抑郁症复发率的动态变化规律。
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