研究了一类具有连续分布延时的反馈神经网络模型的周期解的存在性和全局稳定性。
Both the global exponential stability and the existence of periodic solutions for a class of recurrent neural networks with continuously distributed delays (RNNs) are studied.
稳定性分析是动态反馈神经网络的重要研究内容，对于网络的设计和应用具有指导作用。
Stability analysis is an important topic for dynamical feedback neural networks, which provides certain guidance for the their design and applications.
利用时变反馈神经网络的概念及二维线性系统理论给出了非线性离散系统的一种实时建模方法。
A real time modeling approach for nonlinear discrete time system is presented by using the concept of time variant recurrent neural network and the theory of two dimensional system.
反馈神经网络是神经网络中最重要的类型之一，这种网络的突出特点就是它具有联想记忆的功能。
Feedback neural network is one of the most important neural network, the most remarkable feature of this kind of network is the associative memory function.
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。
According to the research of the recurrent neural network control method application to aeroengines, the system based on recurrent network is built.
对反馈神经网络进行了研究，在分析现有混沌神经网络的工作原理的基础上，提出一种新的混沌神经网络模型。
The study of the feedback neural network, the analysis of the work principle of Hopfield neural network lead to a neural network model with chaotic character .
这就是为什么反馈是非常重要的，所以那些错误的神经网络可以被准确的信息所取代。
This is why timely corrective feedback is important so those faulty circuits can be replaced with accurate information.
提出一种具有神经网络补偿的状态反馈控制方法并用于液压伺服位置控制系统。
This paper proposes a state feedback control strategy with a neural network compensator, which is applied in a hydraulic position servo 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。
With the feedback behavior, the recurrent neural network can catch up with the dynamic response of the system.
同时本文将机器学习和相关反馈结合起来用于图像检索，在实验中使用了K -NN、BP神经网络和支持向量机分类器。
At the same time, we used relevance feedback and machine learning used in image retrieval. K-NN, BP neural network and support vector machine classifiers were used in experiments.
基于人工神经网络的方法，建立了碾压混凝土坝施工期热学参数反馈分析模型。
Based on artificial neural network, thermal parameter feedback analysis model of RCC dam during construction period has been established.
针对输入和输出均为时变函数或过程的实际系统建模和仿真问题，提出一种输入和输出均为时变函数的反馈过程神经网络模型。
In order to model and simulate systems with time-varying functions or processes, a feedback process neural network model with time-varying input and output functions is proposed.
在反馈学习算法的基础上，将模糊逻辑和神经网络自适应控制的结构结合在一起。
The neural network-based adaptive control and fuzzy logic are integrated based on feedback learning algorithm.
它通过构造伪输出辨识被控对象参数，引进反馈误差，实现对解耦神经网络的在线训练。
It can identify the parameters of a controlled object by forming a fake output and bring in a feedback error for performing an on-line training to decouple the neural network.
讨论了一类二元时滞反馈人工神经网络模型。
This paper is concerned with a two-neuron artificial neural network model with delayed feedback.
根据反馈线性化理论，讨论了神经网络自适应非线性动态逆控制设计。
A discussion is devoted to the design of a self adaptive and nonlinear dynamic neural network inversion controller according to the feedback linearization theory.
在闭式循环柴油机配氧反馈控制的基础上采用了神经网络前馈控制策略。
Based on the feedback control, the neural feedforward compensation was applied in oxygen control of closed cycle diesel.
利用神经网络具有自学习的优点，可以大大减少误差反馈问题对工艺数据的需求，并且便于系统的扩展。
Utilize the neural network to have advantage taught oneself to practise, can reduce the error and feedback the demand for the craft data of the question greatly, and benefit systematic expansion.
目的探讨反馈人工神经网络模型预测肾综合征出血热发病率的应用前景。
Objective To study the application of back propagation artificial neural network model in prediction for incidence of hemorrhagic fever with renal syndrome.
利用人工神经网络，讨论了线性定常控制系统关于状态反馈、输出反馈及动态补偿器的极点配置问题。
By Using an artificial neural network, the pole assignment problem of state feedback, output feedback and dynamic output feedback compensators in linear control system are discussed.
该系统包括设定值调节器、神经网络模糊前馈控制器、模糊反馈控制器和单元机组。
The intelligent control system consists of reference governor, neuro-fuzzy feedforward controllers, fuzzy feedback controllers and fossil-fuel power unit (FFPU).
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.
相关反馈方法有许多种，如移动查询向量、修改特征权重、贝叶斯、支持向量、神经网络等。
Such as move query vector, modify the weight of characteristics, Bayesian, SVM, neural and networks.
在全状态反馈的前提下，设计了一种基于在线神经网络和反馈线性化的非线性直接自适应控制器。
A nonlinear direct adaptive controller based on online neural network and feedback linearization is designed by precondition of all state feedback.
神经网络的硬件实现常伴随反馈信号的延时，网络的应用需要对具有时滞反馈网络稳定性的充分研究。
The physical implementation of neural network follows delays of feedback signal and the application of network requires the study of the stability.
针对非匹配不确定性的严反馈块非线性系统，基于神经网络提出一种鲁棒控制方法。
Based on neural networks, a robust control design method is proposed for strict-feedback block nonlinear systems with mismatched uncertainties.
对角神经网络(DRNN)为非全反馈式动态神经网络。
Diagonal recurrent neural network (DRNN) is a non-unity feedback network.
研究了应用神经网络和PD反馈控制实现非线性系统的自适应跟踪问题。
Neural networks and PD feedback controllers for adaptive tracking in nonlinear systems are presented.
结合遗传算法(GA)和误差反馈型神经网络(BP)，建立了优化的GA - BP神经网络预测模型，预测转炉炼钢过程钢液终点磷含量。
Combined Genetic Algorithms (ga) and back-propagation neural network (BP), an optimized GA-BP model was established to predict phosphorus content. Some data were chosen to train the network model.
结合遗传算法(GA)和误差反馈型神经网络(BP)，建立了优化的GA - BP神经网络预测模型，预测转炉炼钢过程钢液终点磷含量。
Combined Genetic Algorithms (ga) and back-propagation neural network (BP), an optimized GA-BP model was established to predict phosphorus content. Some data were chosen to train the network model.
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