在策略迭代结强化学习方法的值函数逼近过程中，基函数的合理选择直接影响方法的性能。
An appropriate selection of basis function directly in? Uences the learning performance of a policy iteration method during the value function approximation.
应用LOO估算选择的核函数模型能够较好地逼近最佳值。
The kernel function model selected by LOO estimation can approach the best value satisfactorily.
只要选用相应的目标函数，曲面插值、逼近、拼接和光顺都可以使用优化技术统一处理。
Optimization techniques are being applied to solve the problems of surface interpolation, approximation, smooth joining and fairing, aiming at corresponding goal functions.
该文将径向基函数网络引入地震数据处理中，实现了函数逼近法地震数据的插值处理，在实际地震数据处理中取得了较好的应用效果。
This paper introduces the radial basis function (RBF) network in the seismic data processing, and realizes the inserting data in seismic data processing with function approximation method.
然后分析了多结点样条插值方法的逼近精度、正则性、插值核函数的频域特性。
Then the accuracy of approximation, regularity of many-knot splines interpolation method and frequency property of the interpolation kernel are worked out for comparison.
利用凝聚函数一致逼近非光滑极大值函数的性质，将非线性互补问题转化为参数化光滑方程组。
By using a smooth aggregate function to approximate the non-smooth max-type function, nonlinear complementarity problem can be treated as a family of parameterized smooth equations.
利用BP网络具有任意逼近非线性函数和内插值特性，提出一种实现常用热电阻阻值-温度变换的新方法。
Put forward a new approach which describe the relationship of resistance-temperature conversion for common thermo-resistance in terms of BP networks has the characteristic of non-linear.
讨论了一类插值有理函数对可微函数的逼近，得到了相应的逼近阶。
The approximation of differentiable functions by a kind of interpolatory rational functions is discussed, and the corresponding order of approximation is obtained.
最后展示了一个具体问题的特征值以及特征函数的逼近解。
Accordingly, some approximate solutions of eigenvalues and eigenfunctions are given.
张力样条插值函数在给定区间上分段逼近真值。
Tension spline interpolation function maintains smoothness on a given interval, and it approaches a true function subinterval by subinterval.
提出了小波函数和普通函数内积数值计算的外推加速算法，给出了外推加速算法的可行性保障定理。结果表明此算法的收敛速度较快， 得到的近似值的逼近效果较好。
In this paper, we give an extrapolation method for integral with wavelet. Theorem can ensure it is possibility. The result show that the method converge quickly, and the approach effect is very good.
采用RBF神经网络逼近系统未知的非线性函数，引入滑模误差对其权值进行在线自适应调整，改善动态性能。
RBF neural network is proposed to approximate unknown nonlinear function. Sliding mode error is used to adaptively tune its weights online. Dynamics performance is improved.
因为似然比检验有着非常好的性质，特别是对大样本量问题，该方法求解出来的p值函数与真实p值函数非常逼近。
Because the likelihood ratio test has very good properties, especially for large sample size problem, the P-value function with this method is approached the true function.
基于光滑的分段多项式函数和插值思想推导出一个新的光滑函数，从而可以更好地逼近正号函数。
We got a new smooth function for approximating the plus function by interpolation base on smooth piecewise polynomial functions.
该类算法的基本思想是通过求解一系列二次函数在信赖域中的极小值点逼近最优化问题的解。
The basic idea of these methods is to approximate the optimization problem by a sequence of quadratic minimization problems subject to some trust region.
另一种是只设置一个在线支持向量机，用来逼近CSPS系统的所有状态-行动对的Q值函数的OSVM - Q - 1算法。
One is OSVM-Q, online SVM is set for each exploration state. The other is OSVM-Q-1, only one online SVM is set for all state-action of CSPS system.
另一种是只设置一个在线支持向量机，用来逼近CSPS系统的所有状态-行动对的Q值函数的OSVM - Q - 1算法。
One is OSVM-Q, online SVM is set for each exploration state. The other is OSVM-Q-1, only one online SVM is set for all state-action of CSPS system.
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