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收敛性

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RIPOPT in FORTRAN performs very well in the solution of rank deficient problems and tests on global convergence and infeasibility identification.

FORTRAN环境下的rIPOPT算法在不满秩系统求解、全局收敛性测试和不可行性识别中表现出良好性能。

It can preserve some infeasible solutions with high quality.

用概率论的有关知识证明了算法的收敛性

It has been prepared for the investigation of inexact quasi-newton method for operator equations in infinite dimensional space.

文献[1]对有限维空间中非线性方程组的不精确拟牛顿法的收敛性进行了研究,为无穷维空间上的算子方程的不精确拟牛顿法的研究作好了准备。

A method of integrating infinite integrals which occur in axisymmetrical field in eddy current testing is presented. Subtraction of asymptotic terms is proposed to speed up the truncation process of an infinite integration interval, which greatly improves the integration of infinite integrals.

本文对涡流检测中解析求解轴对称场时遇到的无穷积分给出一种简单有效的数值积分方法,提出一种改进积分收敛性的方法,加速了无穷积分的截断,显著提高了轴对称场的计算效率。

By using theconvergence properties of infinite matrix in E and the sequentially open sets notion,it pr-esents a criterion for the sequential topological vector spaces.

本文首先借助于E中无穷矩阵的收敛性态及序列开集概念给出了E是序列型空间的刻划。

For the problem of value iteration optimization of the compact action set in semiMarkov decision process, a unified standard VI algorithm directly based on the equivalent infinitesimal generator under both discount and average criteria was proposed with the proof of convergence.

针对半Markov决策过程在紧致行动集上的数值迭代优化,提出了折扣和平均准则下直接基于等价无穷小生成子的统一的标准数值迭代算法,并证明了其收敛性

The conditions that guarantee the existence of constrained points and segments in Voronoi mesh are presented, which puts forward a novel two-dimensional conforming Voronoi mesh refinement algorithm that completes the mesh by setting up initial examining strip set and subdivision of the strip set.

给出了限定点、限定线在Voronoi网格中存在的充要条件,提出了二维限定Voronoi网格细化算法,通过设置初始检测带,然后细分检测带来实现限定Voronoi网格的剖分;同时证明了该算法对于任意平面线段图输入限定条件的收敛性

The results of experiments show that the neural network algorithm solving differential equations with the initial value problem can establish mathematical model, which can be calculated any given point of function, which is any difference method can not do.

针对微分方程初值问题的求解,论文探索性研究了求解微分方程初值问题的神经网络模型算法,并分析了算法的收敛性,为神经网络学习率大小的确定建立了理论依据。

Firstly, Wavelet-Galerkin algorithm for solving the first kind of singular integral equation with the Hilbert kernel is proposed, we use the characteristic of periodic wavelet on L~2([0,1]) and Hilbert kernel to solve and make stiff matrix lower dimensions and become sparser through thresholding,thus the cost of computation is reduced. Because of the singularity of Hilbert kernel we use Tikhonov regularization method to solve the system of stiff equation. At last the convergence and numerical result of approximate solution are given. Secondly, an approach of regularization based on Fourier is presented for sideways heat equation; we give the theory proof and error estimate.

首先,提出了含Hilbert核的第一类奇异积分方程的小波伽辽金(Wavelet-Galerkin)数值算法,该算法中利用了L~2([0,1])上的周期小波和Hilbert核的特点进行处理,使得刚性矩阵维数降低并且通过阈值使得它更加稀疏,减少了计算量;由于Hilbert核的奇异性,通过Tikhonov正则化方法求解所得到的刚性方程组,给出了收敛性和数值结果;其次,对标准的一维逆热传导方程给出了一种基于Fourier正则化方法,给出了理论证明及其误差估计,解决了文献中算法与理论误差估计的不相匹配的现象,该正则化方法不仅保留了测量数据的部分高频成份,且与文献中的算法具有同样的计算量和误差估计。

The calculated results indicate that Chens lattice inversion method was exact for radial interatomic potential of alkali metals with much faster convergence than CGE method.

计算表明,陈氏三维晶格反演比CGE方法具有更快的收敛性,容易获得较高精度的原子间相互作用势。

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