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This thesis discussed the recursive least square algorithm, the linear least square algorithm and recursive orthogonal least square algorithm for the RBPNNs.

文中讨论了递推最小二乘算法、线性最小二乘法和递推正交最小二乘算法用于径向基概率神经网络的训练问题。

S:adaptive filter ; least mean square errors ; orthogonal transform

自适应滤波；最小均方误差；正交变换

This thesis discussed the recursive least square algorithm , M-P pseudo-inverse algorithm and recursive orthogonal least square algorithm for the RBPNNs.

文中讨论了递推最小二乘算法、M-P伪逆算法和递推正交最小二乘算法用于径向基概率神经网络的训练问题。

Based on analyzing regression analysis, neural network and the least square support vector machines that the three soft computing methods fitting for data fitting, in the paper try to use nonlinear regression analysis, the BP neural network based on Levenberg-Marquardt training algorithm, radial basis function neural network on orthogonal least square training algorithm and least square support vector machines for tracking the position of glass plate.

本文在分析适于数据拟合的回归分析、神经网络、最小二乘支持向量机这三种"软计算"方法的基础上，尝试将非线性回归分析方法，基于Levenberg-Marquardt算法的BP神经网络，基于正交最小二乘训练算法的径向基函数神经网络和最小二乘支持向量机应用于玻璃板位的跟踪中。

The main works include five parts:(1) A modified K-means algorithm for optimizing the RBPNNs' structures was proposed;(2) The RBPNNs' structure optimization method based on the orthogonal least square algorithm was proposed that can greatly reduce the computation expense for the structure optimization;(3) Using the GA to perform the whole structure optimization of the RBPNNs was proposed in this thesis, which include simultaneous optimization of the hidden centers and the corresponding controlling parameters of the kernel functions.

主要工作体现在如下三个方面：(1)提出一种改进的 K-Means 算法；(2)提出了基于递推正交最小二乘算法的结构优化算法来训练径向基概率神经网络，从而大大减小了用于结构优化的计算开销；(3)提出使用遗传算法来实现径向基概率神经网络的全结构优化，即隐中心矢量和核函数控制参数同时优化，通过新设计的编码方式、新构造的适应度函数，充分发挥了 GA 的全局搜索性能，使得所优化的径向基概率神经网络的结构趋于最简。

This paper presents in detail principal theory used to solve linear unbiased least variance estimation problem using Givens-Gentleman orthogonal transformation without square root computation and applies the theory to three stage-multiarc estimation.

本文详细介绍了利用不求平方根的Givens-Gentleman正交变换解线性无偏最小方差估计问题的基本原理以及这种方法在卫星激光测距三级复弧估计技术中的具体应用，给出了计算估值协方差的一组新的公式。

By iteratively combining these two procedures we achieve a way of training the configuration of RBFNN. In addition, the algorithm is very robust with respect to the noise level. Simulation experiments show that the proposed algorithms are sound. In chapter 3, which is the extension of chapter 2, the improvements of the architectures of RBFNNs and the solutions of their relating problems are discussed, Firstly, an new distance metric is advanced and a forward orthogonal least square selection procedure is applied to learning the parameters of classification function and selecting the important input nodes.

首先分析了目前存在的同时确定RBFNN结构和参数的方法的缺陷，在此基础上提出了用基于拉马克的进化学说的进化编程算法来改进算法，以克服某些缺陷；然后针对受到严重噪声污染的系统，如何提高RBFNN的泛化能力的问题，利用基于AIC的适应度函数的改进遗传算法学习结构和参数；最后介绍基于MDL原理的方法，将优化网络的结构和参数分为两个阶段：训练和进化，先自适应地改变RBFNN基函数的中心和宽度，同时训练输出线性权值，再用基于MDL原理的适应度函数的标准GA来优化隐层节点，通过交替使用这两过程达到训练RBFNN的结构和参数的目的，该算法具有较强的鲁棒性。

The result shows that all the three polynomials can be used to reconstruct the wavefront correctly, the reconstruction precision of the orthogonal Zemike polynomial in square zone is comparatively better though the difference of the reconstruction precision among the three polynomials is not apparent.

结果表明：对于方形区域上的波前重构，上述三种多项式都能正确地重构出待测波前，它们的重构精度差别不大，相比之下，方域上正交的Zernike多项式的对待测波前的重构精度更高。

Fabric geometrical parameters based on unit cell model and fabric's FVFs based on macro-unit cell model are perfectly fitted to the orthogonal woven fabric with square shape binder path, but there are some differences for the fabric with sine-line binder path which is the more practical shape.

研究发现，单元体法计算的织物结构参数和巨元体法计算的纤维体积含量，对于接结纱呈矩形折线的正交组织机织物是适用的，但对于接结纱呈曲线的实际织物，还存在着一定的误差。

Secondly, a method based on SCADA to revise the parameter of transformers is proposed, in which the data is obtained from the substation SCADA system and is processed by least orthogonal square method, then the fitting calculation of the curve is performed, finally the actual parameters of the transformer can be derived and it can be used as the basic data for the economic operation of the transformer.

通过变电站监控系统得到SCADA实时数据，采用最小正交二乘法，对变压器损耗曲线进行拟合计算，得到变压器实际参数和功率损耗特性，并以此作为变压器经济运行的基础数据。

But we don't care about Battlegrounds.

但我们并不在乎沙场中的显露。

Ah! don't mention it, the butcher's shop is a horror.

啊！不用提了。提到肉，真是糟透了。