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.
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