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。
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。
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。
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。
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。
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。
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。
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。
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。
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。
A new information theory criterion for blind source separation based on a recurrent neural network is proposed.
本文基于一个全连接递归网络结构，给出一种新的信息理论的盲源信号分离准则。
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。
Global asymptotic stability of general recurrent neural network models with S-type distributed delays on infinite intervals.
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。
A scheme of adaptive control based on recurrent neural network is presented for a class of nonlinear systems only with a nonlinear part.
基于递归神经网络给出了仅含一个非线性环节的一类非线性系统的自适应控制方案。
A method based on recurrent neural network compensation Kalman's evaluation error is proposed in order to enhance the evaluation precision.
为了提高卡尔曼滤波估计精度，提出了一种基于回归神经网络补偿卡尔曼滤波器估计误差的方法。
A new training approach for the training algorithm of a fully connected recurrent neural network based on the digital filter theory is proposed.
一种新的基于数字滤波器理论的全互连复值递归神经网络训练方法被提出。
This paper describes the efficiency and restriction of the distribution by the means of math and applies recurrent neural network in the question.
该文用数学的方法描述了资源分配效率和分配的约束条件并将离散反馈网络应用在这个问题中。
According to the research of the recurrent neural network control method application to aeroengines, the system based on recurrent network is built.
根据反馈神经网络控制方法在发动机控制系统中的应用研究，建立了基于反馈网络的发动机控制系统。
As a new type of recurrent neural network, echo state network (ESN) is applied to nonlinear system identification and chaotic time series prediction.
ESN(回声状态网络)是一种新型的递归神经网络，可有效处理非线性系统辨识以及混沌时间序列预测问题。
This paper proposes an internal model control system based on recurrent neural network, and considers jigger layer loose condition as research object.
该文提出一种基于对角递归神经网络的内模控制系统，并以跳汰生产过程床层松散状况为对象进行了研究。
A new recurrent neural network based on B-spline function approximation is presented. The network can be easily trained and its training converges more quickly.
提出一种新的基于基本样条逼近的循环神经网络，该网络易于训练且收敛速度快。
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。
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.
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。
In this paper, the continuous time recurrent neural network is proposed to solve the functional minimization problem, which is often involved in estimation and control.
针对信息科学和控制理论中经常涉及的一类泛函极值问题，提出基于连续回归神经网络的求解方法。
Aiming at the difficulties in modeling the complex MIMO system, the multilayer local recurrent neural network is used to build the predictive model of the process off-line.
针对复杂多变量系统难以建模的问题，采用多层局部回归神经网络离线建立其预测模型。
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.
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。
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。
A new type of adaptive PID controller using diagonal recurrent neural network (DRNN) is presented. An on-line learning algorithm based on PID parameter self-tuning method is given.
提出了一种基于对角回归神经网络的PID控制器结构，给出了PID参数在线自整定的学习控制算法。
A new type of adaptive PID controller using diagonal recurrent neural network (DRNN) is presented. An on-line learning algorithm based on PID parameter self-tuning method is given.
提出了一种基于对角回归神经网络的PID控制器结构，给出了PID参数在线自整定的学习控制算法。
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