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In recent years China economy fast growth, but various local development situation is different. Because the geographical environment and the humanities condition differently creates the city and countryside disparity. Various local growth speedy is different. This empirical study, using the regional data of 204 cities in China between 1996 and 2001, discusses whether exists conditional convergence in China.

摘要 近年来中国大陆在经济上的成就是有目共赌,但境内各地区发展情况却不一致,因地理环境、人文条件不同造成城乡差距,各地区的成长速度不同,本研究以1996年~2001年中国大陆204个地级城市的经济成长率及影响经济成长率之变数资料为基础,探讨中国大陆各城市间是否存在条件收敛

This paper bases on the textbook Solow model, considering the effect of the reform to the economic growth in China. An augmented Solow model that includes accumulation of human capital and institution variables has been established to investigate the conditionalβconvergence of Chinese cross- province economic growth and the rural-urban inequality in China. The following research using econometrics approach indicates that the model establishing in this paper can reflect the Operation of macro-economy movement.

相关实证研究表明本文建立的计量经济学实证模型与中国经济体制改革以来的宏观经济运行情况相吻合,只有考虑了中国经济体制改革过程中的制度变迁因素,才能解释其他国家经济增长过程中普遍存在的地区经济增长β收敛现象在中国没有出现的原因,并对经济体制改革以来中国城乡经济发展不平衡问题的日益恶化作出合理的解释。

In cross-section analysis, there exists conditional convergence in China and spatial error model is better than spatial lag model. In panel data analysis, fixed effect spatial error model is better than fixed effect spatial lag model.

在横断面分析方面,中国大陆地级城市间存有条件收敛,以空间误差模型较佳;Panel Data分析则以固定效果空间误差模型优於固定效果空间落迟模型。

On the other hand, an iterative hard shrinkage algorithm is obtained by using the generalized conditional gradient method, as well as convergent theorems for Solutions and stopping criterion.

此外,利用广义条件梯度法得到了迭代硬阈值算法,并给出了解的收敛性定理和停止准则。

In allusion to the conflict in solving the precision and constringency speed in genetic algorithm, this paper advances a kind of a new genetic algorithm for self adaptation, symmetry and congruity.

针对遗传算法存在求解精度与收敛速度间的矛盾,提出一种自适应对称调和遗传新算法。

The new conic model trust-region subproblem was proposed in 2005, and divided into three different cases.

本文主要讨论锥模型非凸信赖域子问题的求解方法及收敛理论。

Finally, the numerical results show this class of conjugate gradient methods is very efficient.

然后证明三种新算法在强Wolfe线搜索下的全局收敛性,数值验证表明这类共轭梯度法是比较有效的。

In this paper a class of new conjugate gradient methods are presented, with which the global convergence with generalized Wolfe line search is proven.

本文提出一族新的共轭梯度法,证明了其在推广的Wolfe非精确线搜索条件下具有全局收敛性。

The two Armijo-type line searches proposed in Chapter 4 are shown to guarantee the global convergence of the class of conjugate gradient methods.

在第四章提出的两种Armijo型线搜索下,针对不同的线搜索参数分别讨论了共轭梯度法簇的全局收敛性。

A class of conjugate descent algorithm with single parameter βk for unconstrained minimization problems is presented and it is proved that this algorithm is of descent feature when it satisfies the condi- tion of a sort of inexact linear searching and, in addition, it is globally convergent.

给出了无约束问题一族含有一个参数βk的共扼下降算法,证明了该共扼下降算法在满足一种非精确线性搜索条件时是下降的,而且是全局收敛的。同时可以看到共扼下降算法是其特例

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