逼近

Finally, to explain the advantage and shortcoming of nonparametric analysis and parametric analysis, and introduce some main shapes of nonpametric regression model: Fourier series, kernel estimators, and spline smoothing. In the meantime, we give the approximate theory and approximate distribution theory of these methods.

阐述了非参数回归分析和参数回归分析的优缺点，介绍了非参数回归模型的几种主要形式：富氏级数，核估计量和样条平滑，给出了这些方法的逼近理论和逼近分布情况。

Finally,we discuss the waveletapproximation by means of Fourier analysis and establish a series of new re-sults.

这里还探讨了多尺度逼近作为低通滤波器的有关性质。最后，该章用Fourier分析方法讨论了该小波逼近的若干问题，得到了一系列新结果。

In the network method, the neural network with powerful function of approximation is used to get the continuous approximate function of the discrete fringe pattern.

在测量过程中，利用神经网络强大的函数逼近能力，得到离散条纹图的连续逼近函数，从中解出物体的相位分布信息，获得物体的三维面形分布。

Neural networks; Function approximation ; generalized Fourier series ; approximation capability

神经网络；函数逼近；广义Fourier级数；逼近能力

The dissertation focuses on performance gradient estimation and SRO algorithm of DES aswell as other related topics,such as modeling of DES and discrete event simulation,performancemeasure Hessian matrix estimation,Stochastic Approximationand so on.General Semi-Markov Processis adapted to describe behaviour of DES and discrete eventsimulation.A general result is obtained and applied to analyze strong consistency of performancegradient Perturbation Analysisestimator.Conditions for effectiveness of InfinitesimalPerturbation Analysisare also discussed.New PA algorithms,such as server PA,PA usingDirac generalized function,job sequence PA etc.,are proposed to deal with discreteparameters.Furthermore,strategies of combining PA algorithms with certain iterative rules areanalyzed widely in order to optimize DES parameters and some SRO algorithms are constructed toslove DES optimization problems.

论文将DES性能分析领域中性能梯度估计和单运行仿真优化作为主要的研究对象，探讨了与性能梯度估计有关的DES和离散事件仿真过程建模、高阶导数估计以及随机逼近等理论和方法；建立了具有一般性的DES和离散事件仿真的广义半Markov过程模型；获得了分析性能梯度估计量强相合性的理论结果和无穷小摄动分析算法应用的条件；提出了诸如服务台数目的摄动分析、奇异摄动分析、串联生产线和加工车间中工件加工序的摄动分析等一系列摄动的思想和算法，对连续参数和离散参数都进行了深入的研究；对摄动分析算法同优化规则结合实现仿真优化的策略也进行了广泛的分析，构造了新型的变界截尾的随机逼近算法，并用于DES的单运行仿真优化研究；最后，给出了DES性能分析方法的实证性研究结果。

Then, the system is linearized by variational approach, the local null controllability is proved by applying a generalized implicit function theorem and combining the good property of the solution mapping.

首先通过对系统线性化，构造泛函，利用对偶方程，给出控制函数具体形式的办法得到系统的逼近能控性；然后采用变分方法对系统线性化，再结合解映射好的性质，应用推广的隐函数定理，证明系统的局部零能控性；最后利用局部零能控性和逼近能控性结合给出系统零能控的结论。

The effects of the initial values and the network approximation error using neural network model composed of feedforward neural net and delayed output feedback in the approximation of NARMAX system are studied, and a conclusion is drawn that under some weak conditions the output of the network model has little difference from that of the actual system.

研究了用带有延迟环节的前馈网组成的网络模型逼近NARMAX系统时网络逼近误差及运行初始误差对网络模型输出的影响，指出在一些弱的条件下网络模型输出与实际系统输出间相差不大。

There are substantial relation between the interpolation and approximation of functions.The interpolation polynomial is regarded as the important tool of achieving approximation of function.

函数插值与函数逼近有着密切的联系，插值多项式可看作实现函数逼近的一种重要工具。

As CMAC neural network could not be used to approximate the multi-valued mapping of an inverse hysteresis directly, an inverse hysteretic operator was proposed to transform the multi-valued mapping into a one-to-one mapping which could enable neural networks to approximate the behavior of an inverse hysteresis.

由于CMAC神经网络不能够直接逼近滞回逆这种具有记忆性的多映射现象，通过引入一个滞回逆算子，将多映射的滞回逆转换成一一映射，然后运用CMAC神经网络控制器来逼近这个一一映射，从而建立一个基于CMAC神经网络的滞回逆模型。

In this paper,we give the error expressions of piecewise linear Lagrange polynomial interpolation and piecewise cubic polynomial interpolation using the Taylor expansions.

中文摘要：本文利用Taylor展开得到三角形上线性Lagrange插值和三次Lagrange插值的导数余项公式，对这些余项公式进行分析，给出了两类能以四阶精度逼近被插函数在对称点的导数值的格式，一种是在均匀剖分时其分片线性插值的相邻单元的导数值的后处理格式，一种是在六片强正规剖分时的三次插值在对称点上的导数值的后处理格式，使得在已知原函数在各节点的值后，通过一个简单的线性计算就可得到原函数在对称点的导数的一个超逼近值，将以往提出的平均导数的二阶精度提高到四阶。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。