第五章总结了本文所做的工作，得到的主要结果及对离散神经网络模型的进一步研究方向。
In Chapter 5, we summarized the main results of this thesis and further research direction of the discrete neural networks model.
基于混沌神经网络模型可以有效地解决高维、离散、非凸的非线性约束优化问题。
The Chaotic neural network model can be used to solve many multi-dimensioned, discrete, non-convex, nonlinear constrained optimization problems.
针对多变量非线性离散时间系统设计多模型神经网络解耦控制器。
A multiple models neural network decoupling controller is designed to control the multivariable nonlinear discrete time system.
讨论了利用仅含一个隐层的前馈多层神经网络来辨识离散时间非线性动态系统时的模型检验问题。
This paper investigates the problem of the model validation in identifying discrete-time-nonlinear dynamic systems by using neural networks with a single hidden layer.
几十年来，非线性差分方程理论已广泛应用于计算机科学、经济学、神经网络、生态学及控制论等学科中出现的离散模型。
In the last decade, nonlinear difference equation theory has been widely applied in the discrete models of computer science, economy, neutral net, ecology and control theory.
将神经网络、遗传算法、三轴实验和离散元数值模拟相结合，用于改性砂土等效离散元接触模型参数反演。
The inversion method combining the genetic neural network and the discrete element simulation of triaxial tests is proposed for determining the contact model parameters of the conditioned soil.
然后介绍了如何使用模糊聚类算法和等价的前馈神经网络从样本数据中辨识离散的TS模型。
Then we introduce how to identify the TS model from sample data using fuzzy clustering algorithm and equivalent feedforward neural network.
本文研究了一类二元离散人工神经网络模型的解的收敛性及周期解的存在性等动力学特征。
This thesis has studied the dynamic features of a class of the discrete-time neural network model of two neurons, such as the convergence and periodicity and etc.
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.
针对一类不确定的离散时间非线性非最小相位动态系统，提出了一种基于神经网络和多模型的直接自适应控制方法。
A direct adaptive control approach is proposed for a class of uncertain discrete time nonlinear non-minimum phase dynamical systems.
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.
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.
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