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The analysis is relatively simple due to the good approximation and the compact expression of the spline function.

由于样条函数有良好的逼近性及紧凑性,使得层合板在脉动流这种复杂荷载作用下的动力分析也相对简单。

The primary contributions of this paper contain the following points: 1 Research the advantages and disadvantages of the traditional methods of spline curve, surface interpolation and approximation algorithm.

本文的主要研究成果包括: 1 研究了传统的样条曲线、曲面的插值算法、逼近算法的优、缺点。

Spline functions can be used to approach arbitrary continuous curves with high accuracy.

样条函数以其特有的优点可以用来逼近任意的连续曲线,且具有很高的精度。

Many infinite-horizon optimal problems encounter in management scienceand economics have solutions that approach some stationary value for the state variable.

在科学管理和经济中,许多无穷维最优控制问题对于状态变量存在逼近到一些稳定值的解。

The numerical calculation commonly used for the Delphi process more than 100, including solutions of linear algebraic equations, interpolation, numerical integration, special, function approximation, eigenvalue problems, data fitting equation Root and solve nonlinear equations, functions and the extreme optimization, statistical data description, Fourier transform spectra, solution of ordinary differential equations reconciliation partial differential equations.

本书共有数值计算中常用的Delphi子过程100多个,内容包括解线性代数方程组、插值、数值积分、特殊函数、函数逼近、特征值问题、数据拟合、方程求根和非线性方程组求解、函数的极值和最优化、数据的统计描述、傅里叶变换谱方法、解常微分方程组和解偏微分方程组。

On the basis of the principle of the least-squares approximation and steepest descent method and the average of the given discrete points, the space linear fitting can obtained, at the same time through a test proved the algorithm is correct.

其中空间直线拟合根据最佳平方逼近原理和最速下降法以及所给离散点的均值求得,并通过试验验证了此算法运算结果的正确性。

Then, the stochastic approximation method is applied to determine the optimal control parameters.

应用扰动分析法得到性能指标对控制参数的灵敏度估计,并证明了估计的无偏性,又利用随机逼近技术优化控制参数。

1Because some conditions can not be fulfilled,one can not applythe known results in stochastic approximation directly.

1由于有些条件不能满足,现有的随机逼近结果无法直接利用,我们巧妙地克服了这一困难,在较弱的条件(文中H.4.1—H.4.3)下,给出了这类算法的严格收敛性分析(定理4.3.2,定理4.3.3)。

Then, an online optimization algorithm that combines policy gradient estimation by learning and stochastic approximation is derived.

利用此模型的动态结构特性,结合在线学习估计梯度与随机逼近改进策略,提出适应带宽配置在线优化算法。

Then by utilizing the features of this model an online optimization algorithm that combines policy gradient estimation and stochastic approximation is derived.

利用此模型的动态结构特性,结合在线学习估计梯度与随机逼近改进策略,提出动态电源管理策略的在线优化算法。

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