共轭梯度法

The examples indicate that the algorithm has strong pertinence and high efficiency, hi the discrete variable optimization, the problem is solved in the relative quotient method On the base of analyzing the relative quotient method, the conjugate gradient direction is used to modify the old search directions, the iterative matrix of the algorithm, and the method to resolve the discrete variable optimization, the relative conjugate difference quotient algorithm is presented.

离散变量优化算法是从相对差商法开始的，在详细分析相对差上法的基础上，用共轭梯度方向修正原有的搜索方向，并对算法的迭代矩阵进行相关的修改，最终形成一种用于求解离散变量优化问题的RCDQ法。

The path is defined as linear combination of a sequence of conjugate directions whichare obtained by applying standard conjugate direction method to approximate quadratic functionof unconstrained optimization.

Bulteau和Vial在[7]中构造了无约束最优化问题的共轭梯度路径，其基本思想是将标准共轭方向法应用于无约束优化目标函数f的局部二次近似函数，得到一组共轭方向序列。

We mainly investigate cyclic correlator and conjugate gradient algorithm are investigated mainly and applied in joint detection.

主要研究了圆周相关器法和共轭梯度算法，并将它们用于联合检测。

Thirdly, in order to improve the learning efficiency and stability of feedforward neural network, a fast learning algorithm for neural networks based on CGM-OC approach is presented. Compared with other learning methods such as BP method, Broyden Flecher Goldfarl Shanno method and Powell method in which the derivative is replaced by the difference quotient etc, simulation results show that the proposed method is an efficient and fast one.

第三，为了提高前馈神经网络权值的学习效率及稳定性，提出一种基于正交校正共轭梯度优化方法的神经网络学习算法，通过与其它学习算法（如：BP算法、变尺度法、用差商近似代替导数的Powell法等）的比较，经仿真试验表明，本算法是一种高效、快速的学习算法。

It is also the base of structure optimization.According to main object characteristics of structural dynamics design,structuraleigenveetor sensitivity computation is,first,be studied.A Neumann series expansionmethod is proposed in accordance with the modal method and is developed to agreewith the structure with rigid body modes.A rapid Neumann series expansion methodfor eigenvector sensitivity is formed;it may greatly improve the efficiency ofcomputing eigenvector derivation.

本文根据结构动力学设计的主要目标特性，首先进行了结构特征向量灵敏度分析研究：形成了计算特征向量灵敏度的Neumann级数展开法，并将其扩展到适用于具有刚体模态的结构特征向量灵敏度分析；研究出计算特征向量灵敏度的快速Neumann级数展开法，该方法大大提高了特征向量灵敏度分析的效率；建立了无需K-1运算的结构特征向量灵敏度分析的共轭梯度迭代法。

BiConjugate Gradients Stabilized method is applied for solving large linear equation set. That the calculation results of PC modeling program match well with that of parallel algorithm shows high reliability of the latter. The parallel algorithm has established the basis for the inversion 3D Borehole-Surface electromagnetic data and also provided the tech support for the utilization of the program.

在求解大型线性方程组时，采用的是稳定的双共轭梯度算法，单机正演程序与并行正演程序的计算结果有着很好的一致性，这说明了并行算法的正确性，为进一步开发井地电法三维反演并行程序奠定了基础，也为井地电法三维正、反演程序实用化提供了技术支持。

The VSP-CDP imaging and Kirchhoof migration method were employed to get the fine profile of the upgoing wave.

采用最小平方共轭梯度法进行速度层析反演，得到井间反射波成像的速度模塑，利用VSP-CDP成像与克希正夫偏移相结合的方法对井间地震上行反射波进行精细成像。

The VSPCDP imaging and Kirchhoof migration method were employed to get the fine profile of the upgoing wave.

采用最小平方共轭梯度法进行速度层析反演，得到井间反射波成像的速度模型，利用VSPCDP成像与克希霍夫偏移相结合的方法对井间地震上行反射波进行精细成像。

The inverse problem is solved using conjugate gradient method of minimization based on discrete ordinates method of radiative transfer equation.

该方法是在辐射传递方程离散坐标近似的基础上，用求目标函数极小值的共轭梯度法进行反演计算。

The real data verification shows that the wavelet, reflection factor and acoustic impedance given by PCGA are more accurate, quicker convergent and value stable than the existing direct sparse inversion method.

用实际数据检验算法，表明预条件共轭梯度法反演的子波、反射系数和波阻抗要比直接稀疏反演精度高、收敛快、数值稳定。

Plunder melds and run with this jewel!

掠夺melds和运行与此宝石！

My dream is to be a crazy growing tree and extend at the edge between the city and the forest.

此刻，也许正是在通往天国的路上，我体验着这白色的晕旋。