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.
本文主要运用一种具有全局收敛性的单调迭代法求解了一类非线性扩散方程的数值解。
This paper mainly studies the numerical solution of a class of nonlinear diffusion equations using a monotone iteration method with the global convergence.
为此，用全局归一化的局部方差度量空间细节，得到新的扩散系数。
Therefore, global variance normalized was proposed to measure spatial detail, and then a new diffusion coefficient was given.
讨论了一类带有扩散和具有阶段结构与时滞的两种群捕食系统，分析了该系统的非负不变性、边界平衡点性质及全局渐近稳定性。
A system of retarted functional differential equations as a predator-prey model with stage structure and dispersion is discussed. Conditions for global stability of the system are given.
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.
在求解全局优化问题时，通常免疫算法、进化扩散算法分别在局部搜索和全局搜索方面表现较弱。
In solving global optimization, immune algorithm is usually weak in local search, while evolutionary diffusion optimization is weak in global search.
在求解全局优化问题时，通常免疫算法、进化扩散算法分别在局部搜索和全局搜索方面表现较弱。
In solving global optimization, immune algorithm is usually weak in local search, while evolutionary diffusion optimization is weak in global search.
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