收敛性的

NA samples ; the kernel estimation of density function ; empiricale Bayes test ; asymptotic optimality ; convergence rates

NA样本；密度函数的核估计；经验Bayes检验；渐近最优性；收敛速度

Bring forward a kind of learning algorithm fitting on the base of spline function, because the spline function has good flexibility and quadratic smoothing property, the search problem of network weight functions training can be converted into the resoluting extreme value problem of the plurality function through using spline function to represent network input and link weight functions, thus the PNN can be trained with the help of the existing neural network learning algorithms;④build a kind of learning algorithm base on the alternate of Walsh function, the complexity of network computing can be decreased through using the complete orthogonality of Walsh function corollary.

应用结果表明该算法收敛速度快，稳定性好；③提出了一种基于样条函数拟和的学习算法，由于样条函数具有很好的柔韧性和二次光滑性，将网络输入函数和连接权函数用样条函数的形式表示，可把网络权函数训练的函数寻优问题转换为多元函数求极值的问题，从而可借助于现有的神经网络学习算法训练过程神经元网络；④建立了一种基于Walsh函数变换的学习算法，利用Walsh函数系的完备正交性，可大大降低网络计算的复杂度。

Finally, in the third section, by constructing some functional which similar to the conservation law of evolution equation and the technical estimates, we prove that in the inviscid limit the solution of generalized derivative Ginzburg—Landau equation converges to the solution of derivative nonlinear Schrodinger equation correspondently in one-dimension; The existence of global smooth solution for a class of generalized derivative Ginzburg—Landau equation are proved in two-dimension, in some special case, we prove that the solution of GGL equation converges to the weak solution of derivative nonlinear Schr〓dinger equation; In general case, by using some integral identities of solution for generalized Ginzburg—Landau equations with inhomogeneous boundary condition and the estimates for the L〓 norm on boundary of normal derivative and H〓 norm of solution, we prove the existence of global weak solution of the inhomogeneous boundary value problem for generalized Ginzburg—Landau equations.

第三部分：在一维情形，我们考虑了一类带导数项的Ginzburg—Landau方程，通过构造一些类似于发展方程守恒律的泛函及巧妙的积分估计，证明了当粘性系数趋于零时，Ginzburg—Landau方程的解逼近相应的带导数项的Schr〓dinger方程的解，并给出了最优收敛速度估计；在二维情形，我们证明了一类带导数项的广义Ginzburg—Landau方程整体光滑解的存在性，以及在某种特殊情形下，GL方程的解趋近于相应的带导数项的Schr〓dinger方程的弱解；在一般情形下，我们讨论了一类Ginzburg—Landau方程的非齐次边值问题，通过几个积分恒等式，同时估计解的H〓模及法向导数在边界上的模，证明了整体弱解的存在性。

The new method has monotone consistency, convex consistency, linear transformation consistency, gradually approaching white exponential law coincidence property and linear convergence rate.

结果表明，这一方法不仅保持了原方法的升凹一致性、线性变换一致性，而且具有渐近白指数律重合性和线性收敛速度。

To enhance the robustness of DTS, the solution with the minimum error is taken as the result when convergence cannot be found.

算法在不收敛情况下以误差最小解为计算结果，提高了DTS的鲁棒性。

Due to the fact that the method based on local linearization is usually lost in local minimum values and the optimization solution is dependent on the selection of initial solution,the standard genetic algorithm has po...

该算法利用拟网格法初始种群和综合交叉策略，克服了早熟收敛现象，从而提高了遗传寻优的效率。理论模型反演与其它方法比较，结果说明遗传算法具有不依赖初始模型，不容易陷入局部极小，多点多路径概率搜索，以及隐含并行性等优点。

In the third chapter,we study the rate of convergence of nonhomogeneous Markov chains and the absolute average strong ergodic.

第三章研究一类非齐次马氏链的收敛速度及绝对平均强遍历性。

A series of methodes were taken in programming to improve placidity and to quicken convergence rate.

算法实现过程中，采取有效措施提高网络学习的平稳性，加快收敛速度。

The differential evolution algorithm is one kind of global optimization methods with strong robustness, rapid convergence and higher accuracy.

微分进化算法属于全局最优化算法，具有鲁棒性强、收敛速度快、计算精度高的优点。

This dissertation adopts two new variables, the congestion probability and the congestion distance, which provide new metrics for describing the congestion situation, and present a theoretical basis for the dropping probability of packets in the random early detection.

通过与其它数据流和传输协议性能的分析和比较，这一方法表现出了很好的TCP友好性、快速收敛的公平性、高效的资源利用率和平滑性，并且还具有缓解网络数据流的突发性等性能。

This one mode pays close attention to network credence foundation of the businessman very much.

这一模式非常关注商人的网络信用基础。

Cell morphology of bacterial ghost of Pasteurella multocida was observed by scanning electron microscopy and inactivation ratio was estimated by CFU analysi.

扫描电镜观察多杀性巴氏杆菌细菌幽灵和菌落形成单位评价遗传灭活率。