讨论了一类具自反馈二元时滞神经网络模型的渐近行为 。
We consider a network of two neurons with feedback and delay.
研究一类具有不对称互连结构的广义时滞神经网络的动态行为。
The dynamic behavior of a class of generalized neural networks with time delay and asymmetric (interconnecting) structure is investigated.
对不确定变时滞神经网络系统的鲁棒控制器的设计进行了分析。
Design for robust controller of uncertain neural network with time-varying delay was analyzed.
受到自适应控制方法的启发本文提出了一种变时滞神经网络的同步和镇定的方法，并且可以基于同步对其连结权重进行估计。
Motivated by the idea of adaptive control, we proposed a scheme for the synchronization, synchronization-based parameters identification and stabilization of neural networks with time-varying delay.
第四章研究了时滞细胞神经网络的稳定性。
第二章是研究一类无穷时滞微分系统，此系统在生物，神经网络等领域中都有广泛应用。
In the second chapter, we study an infinite delay differential equation, the system was widely applied in the biology, neural network and some other fields.
应用神经网络预测结构响应可以解决主动控制中的时滞问题，为控制决策提供依据。
Applying neural network to predict structural response may solve the problem of time lag in active control and offer basis for controlling decision.
研究了一类随机变时滞递归神经网络的几乎指数稳定性问题。
The almost surely exponential stability of stochastic recurrent neural networks with time-varying delays is investigated.
利用适当的李亚普若夫泛函，研究了时滞分流抑制型细胞神经网络的周期解的指数稳定性。
By means of suitable Lyapunov functionals, the exponential stability of periodic solutions for shunting inhibitory cellular neural networks(SICNNs)with delays and variable coefficients is studied.
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.
研究了带时变时滞的递归神经网络的全局渐近稳定性。
The problem of the globally asymptotical stability of recurrent neural networks with time varying delay is investigated.
研究了一类具有S -分布时滞的区间细胞神经网络的全局渐近鲁棒稳定性问题，得到了实用有效的判别准则并给出了实例。
The global asymptotic robust stability of interval cellular neural networks with S-type distributed delays is investigated. The convenient criteria and an example are presented.
研究一类离散和分布时变时滞的混沌神经网络的广义投影同步问题。
In this paper, the problem of general projective synchronization of a class of chaotic neural networks with discrete and distributed time-varying delays is investigated.
研究了一类时滞离散神经网络指数稳定及鲁棒稳定问题。
The problem of exponential stability and robust stability for a class of discrete-time neural network with time-varying delay is investigated.
因此，神经网络对于时滞系统的控制具有重要的意义。
So Neural Network has great significance to the control of a system with time-delay.
研究方向包括时滞微分方程和反应扩散方程理论及其在神经网络和生物动力系统方面的应用。
My current research interests include theory of delay differential equations and reaction-diffusion equations and also their application to neural networks and biological dynamic systems.
在此基础上，又设计了模糊神经网络预测控制器，实现了对非线性、大时滞系统高精度的自适应控制。
On the basis of this, a fuzzy-neural forecast controller is designed and robust adaptive control to the nonlinear big-lagged chaos system is realized.
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.
在对神经网络的激励函数的三个假设下，研究了具有离散时滞的神经网络的稳定性。
We analyze global stability of a class of neural networks with discrete delays under three assumptions of activation functions.
第四章研究了一类具有反应扩散项的分布时滞模糊bam神经网络的全局渐近稳定性。
Chapter 4 introduces global asymptotic stability of a class of fuzzy BAM neural networks with distributed delays and reaction-diffusion terms.
针对数字电路路径时滞故障测试生成较难的问题，提出了基于神经网络的数字电路路径时滞故障测试生成算法。
A path delay fault testing generation algorithm for digital circuits based on neural network is proposed because the testing generation for path delay fault in digital circuits is more difficult.
运用MATLAB辨识工具箱和神经网络理论，通过对暖通空调系统中常见的时滞对象的辨识，研究了基于神经网络的线性和非线性的辨识方法。
Based on identifying the time-delay system of HVAC, the paper researches the linear and nonlinear systems identification methods with MATLAB system identification toolbox and neural network theory.
提出一种新的神经网络模型—时滞标准神经网络模型(DSNNM)，它由线性动力学系统和有界静态时滞非线性算子连接而成。
A novel neural network model, named delayed standard neural network model (DSNNM), is proposed, which is the interconnection of a linear dynamic system and a bounded static delayed nonlinear operator.
基于相空间重构的非线性预报思想，建立一个时滞的BP神经网络模型，采用贝叶斯正则化方法提高BP网络的泛化能力。
Based on nonlinear prediction ideas of reconstructing phase space, this paper presents a time delay BP neural network model, whose generalization is improved utilizing Bayes' regularization.
从而，研究和应用允许系数和参数在一定范围内涨落的DCNN——时滞区间细胞神经网络是十分必要的。
So it is necessary to study the DCNN system whose coefficients and parameters have their own rangeability.
时滞、参数不确定性和随机噪声都将在相当大的程度上影响神经网络的整体性能，产生振荡行为或其它失稳现象甚至出现混沌现象。
So, time delays, parameter uncertainty and stochastic disturbances may affect the stability of the system, even lead to instability, oscillation or chaos phenomena.
第三章研究了一类具有变时滞的模糊bam神经网络模型的全局指数稳定性。
Chapter 3 introduces global exponential stability of a class of fuzzy BAM neural networks with variable delays.
第三章研究了一类具有变时滞的模糊bam神经网络模型的全局指数稳定性。
Chapter 3 introduces global exponential stability of a class of fuzzy BAM neural networks with variable delays.
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