非线性不等式组的光滑近似方法及其收敛性

将非线性不等式组的求解转化成非线性最小二乘问题,利用引入的光滑辅助函数,构造新的极小化问题来逐次逼近最小二乘问题.在一定的条件下,文中所提出的光滑高斯-牛顿算法的全局收敛性得到保证.适当条件下,算法的局部二阶收敛性得到了证明.文后的数值试验表明本文算法有效.     

一个高精度收敛的变系数微分方程精确解析法*

文[1]给出精确解析法,可用于求解任意变系数微分方程,所得到的解具有二阶收敛精度.在此基础上,本文以变截面梁弯曲为例,给出一个高精度的算法.不增加工作量的情况下可达到四阶收敛精度.具有计算快,简单等特点,文末给出算例,仅用很少的单元即可获得高的收敛精度,表明了本文理论的正确性.     

含指数项广义平方映射的分岔和吸引子

由平方映射延伸构造出了一类含指数项的广义平方映射,并由一维映射通过一次耦合项得到了二维映射.利用一参数分岔图、二参数动力学行为分布图、映射迭代曲线和吸引子相图等方法对这类广义平方映射进行了分析和仿真.研究结果表明：一维广义平方映射分布在一个单位区域内的,有着与单峰平方映射相类似的非线性动力学现象;而二维广义平方映射则存在Hopf分岔和锁频等现象,有着复杂多变、形状奇异的极限环和混沌吸引子. 关键词： 广义平方映射 分岔 迭代曲线 吸引子     

带有势的Schrodinger方程解的点态收敛性

本文将考虑Schrodinger方程：iρ／ρtu(x,t)=△u(x,t) v(x)u(x,t)的解沿光滑曲线γ（x,t）的点态收敛性，从而部分改进了[3],[5]和[8]的结论。     

非线性时滞反应扩散有限差分方程组的高阶单调迭代方法

对一类非线性时滞反应扩散方程的有限差分方程组建立了一类高阶单调迭代方法.这类方法给出了一个有效的线性迭代算法.迭代序列单调收敛于方程组的唯一解,并且序列的单调性使得每一步迭代都给出了解的改进的上下界.迭代收敛率具有p+2阶,这里p≥1是一个正整数,它依赖于迭代方法的构造.数值结果显示了方法的有效性.     

Derivative of Electron Density in Non-Equilibrium Green's Function Technique and Its Application to Boost Performance of Convergence

The non-equilibrium Green＇s function （NEGF） technique provides a solid foundation for the development of quantum mechanical simulators. However, the convergence is always of great concern. We present a general analytical formalism to acquire the accurate derivative of electron density with respect to electrical potential in the framework of NEGF. This formalism not only provides physical insight on non-local quantum phenomena in device simulation, but also can be used to set up a new scheme in solving the Poisson equation to boost the performance of convergence when the NEGF and Poisson equations are solved self-consistently. This method is illustrated by a simple one-dimensional example of an N＋＋ N＋ N＋＋ resistor. The total simulation time and iteration number are largely reduced.     

非线性不适定问题一种双循环的牛顿型迭代格式

本文研究非线性算子方程F(x)=y的解,结合最速下降法,Newton-Landweber迭代格式及正则化思想,在F满足适当的条件下,构造出新的双循环迭代格式。本文对格式的收敛性进行了严格论证,并估计出迭代格式的收敛精度。     

GLOBAL EXPONENTIAL STABILITY IN HOPFIELD AND BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH TIME DELAYS

Without assuming the boundedness, strict monotonicity and differentiability of the activation functions, the authors utilize the Lyapunov functional method to analyze the global convergence of some delayed models. For the Hopfield neural network with time delays, a new sufficient condition ensuring the existence, uniqueness and global exponential stability of the equilibrium point is derived. This criterion concerning the signs of entries in the connection matrix imposes constraints on the feedback matrix independently of the delay parameters. From a new viewpoint, the bidirectional associative memory neural network with time delays is investigated and a new global exponential stability result is given.