目的研究一类细胞神经网络。
第四章研究了时滞细胞神经网络的稳定性。
主要研究了一类细胞神经网络的稳定性问题。
The stability of a general class of cellular neural networks is discussed.
因此稳定性是细胞神经网络可靠工作的前提。
Therefore, the stability is precondition of credibility work for CNNs.
④讨论了细胞神经网络一些可应用于密码设计的性质。
Some properties of cellular neural networks, which are fit for cryptography application, are discussed.
所有的CA规则都可以用细胞神经网络(CNN)实现。
All the ca rules can be implemented with Cellular Neural Network (CNN).
本文用双层的细胞神经网络(CNN)进行盲信号分离。
In this paper a two-layer cellular neural network (CNN) is used to separate blind signals.
同时现实生活也给细胞神经网络提出了更多的问题，比如脉冲现象。
At the same time, the real world also ask cellular neural network to solve more and more problems, such as impulsive phenomenon.
由于细胞神经网络的潜在应用前景，它现已成为神经网络研究的新热点。
The research of cellular neural networks (CNN) has become a hot topic in the area of neural networks for its great potential applications.
本文研究了具有时滞的细胞神经网络周期解存在性和平凡解的稳定性问题。
In this paper, the problem of periodic solutions and stability of Cellular Neural Networks with delay is studied.
本文给出了带阶梯输出函数的细胞神经网络（CNN）的稳定性定理。
This paper presents the stability theorem of cellular neural networks(CNN) with a multi-step output function.
针对多层细胞神经网络模型，分析了其一般状态解并对其动力值域作了估计。
Utilizing the theory of the Drazin inverse, we studied the expression of the general state solution of Multi-layer Cellular Neural Networks.
本文主要研究的是细胞神经网络(CNN)模板的设计及其在图像处理上的应用。
In this paper, we lay primary emphasis on the template design and application in image processing of cellular neural networks (CNN).
但是对于具有脉冲的细胞神经网络所具有动力学性质，现阶段所得的成果还比较少。
However, the results about the dynamic properties of cellular neural network with impulse are still relatively rare.
细胞神经网络由于其连续时间的特性，因此在图象处理和图形辩识方面有着潜在的应用。
Cellula Neural Network has potential applications in image processing and recognizing because of its property of continuous time.
因此，有必要研究细胞神经网络在视频序列图像中目标分割和追踪的应用及其相关算法。
So, it is necessary to study the segment and the tracking of moving object in video image.
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.
摘要研究了具反应扩散有限连续分布细胞神经网络的平衡点的存在性及全局指数稳定性问题。
The existence of the equilibrium point and global exponential stability of distributed delays neural networks with reaction-diffusion terms are investigated in this paper.
已有文献证明，延时细胞神经网络的收敛性与细胞神经网络收敛性研究的难度不是一个数量级。
The early literatures have shown that the research difficulty in delayed Cellular Neural Networks is much more than non-delayed one.
研究了一类带有离散和分布时间滞后的不确定时滞细胞神经网络(DCNN)的全局渐进稳定性。
The global asymptotic stability for a class of uncertain delayed cellular neural networks (DCNN) with discrete and distributed time-varying delays is studied in this paper.
第三章对变系数离散时间混合时滞细胞神经网络模型周期解的存在性与全局指数稳定性进行了讨论。
In Chapter 3, we discuss the existence and global exponential stability of periodic solutions for discrete-time cellular neural network with mixed delays and variable coefficients.
而在处理实际问题时，有必要在细胞间引入信号传输延迟，这种带延迟项的系统称为延时细胞神经网络。
It's necessary to induce delays, among cell when transmitting information in solving real problems. This is so called Delayed Cellular Neural Networks (DCNNs).
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.
设计细胞神经网络模板参数的鲁棒性定理，该定理提供了一组参数不等式以确定满足该功能的参数变化区间。
The robust CNN template was designed, which provided a group of parameter inequality to satisfy its parametric change interval.
通过大量的模拟仿真，提出了非对称细胞神经网络完全稳定的充分条件，并就二细胞神经网络的情况给予了证明；
The paper given some sufficient conditions of complete stability of nonsymmetric cellular neural networks based on plenty of simulation and proves the case of two-cell CNNS.
本文主要研究了细胞神经网络无时滞和有时滞的几类模型的稳定性和基于离散细胞神经网络在图像处理方面的应用。
In this paper, some theorems of stability for several kinds of CNNs are proved and applications in image processing are also obtained.
细胞神经网络(CNN)是图像处理的有力工具。它已用于人工视觉，录像压缩，图像融合、运动和图形识别等领域。
The cellular neural network (CNN) is a powerful tool for image processing and has been used for artificial vision, video compression, image fusion, motion and pattern recognition.
由于细胞神经网络具有高速并行运算、便于硬件实现等特点，因此这种方法在图像实时处理中也具有很大的潜力和应用前景。
Because the cellular neural networks are uniquely suitable for the high-speed parallel computation and easy to implement in hardware, this model has more potential in real-time image processing.
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.
移动目标的识别是本文的一个难点和重点，目前国外的相关研究中，细胞神经网络大多用在图像的初级处理上，识别过程用其它方法实现，如基于DSP算法。
The recognition of moving object is important and difficult. Now, CNN has been used for image primary processing abroad, and the processing of recognition uses other methods such as DSP algorithm.
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