利用共轭梯度方法实现了激发极化（IP）三维快速反演。
Rapid 3D induced polarization (IP) inversions algorithm are developed using conjugate gradient (CG) relaxation techniques.
它在理论上是多项式算法，并可以从任意点启动，可以应用共轭梯度方法有效地求解大规模线性不等式组问题。
SDNM is a polynomial time algorithm with the Newtons method, so that SDNM can solve large-scale linear inequalities.
第一章，回顾有关共轭梯度方法的基本知识及一些著名成果，描述了BFGS和BFGS - TYPE公式。
In Chapter 1, we recall the foundational knowledge about conjugate gradient method and some famous researches, and describe the BFGS and BFGS-TYPE formulas.
程序中采用了“共轭梯度——最小二乘”优化方法，其收敛性能较好，在较坏的初值情况下也能较快收敛。
In this program, the optimization method of "Conjugate Gradient-Least Squares" is employed, since it usually gives good convergent results.
共轭梯度法是最优化中最常用的方法之一，它具有算法简便、不需要矩阵存储等优点，十分适合于大规模优化问题。
Conjugate gradient method, which can be easily computed and requires no matrix storage, is one of the most popular and useful method for solving large scale optimization problems.
共轭梯度法是求解无约束优化问题的一类有效方法。
The conjugate gradient method is one of the most efficient methods for solving unconstrained optimization problems.
利用优化问题的非线性共轭梯度法与混沌优化方法相结合，提出了一种新的混合优化算法。
A new hybrid algorithm which combines the chaos optimization method and the nonlinear conjugate gradient method approach having an effective convergence property is proposed.
针对包装印刷传动位置伺服系统，介绍一种基于共轭梯度学习算法的神经网络自适应PID控制方法。
The paper proposes an adaptive neural network PID controller based on weighlearning algorithm using the gradient descent method for the AC position servosystem of binding and printing.
该方法选取共轭梯度反演算法为拟三维反演的核心。
The conjugate gradient method was selected as the inversion kernel.
结合共轭梯度法，借助于MATLAB软件，提出一种控制系统校正环节优化设计的新方法。
A new method of optimisation design for the correction element in control system is stated by combining the conjugate gradient method and using MATLAB software.
共轭梯度法是求解大规模无约束优化问题的一种有效方法。
Conjugate gradient method is an efficient method in solving problems with unconstrained optimization, which is especially efficient in dealing large dimension.
给出了使用共轭梯度直接最优控制解法与本文方法的结果比较，表明本文方法是解决该类问题的一种直观有效的途径。
Compared with direct conjugate gradient optimal control solution method, the method of this paper is a direct and effective way to solve the problem.
该方法利用最大似然准则建立目标函数，同时利用非线性共轭梯度法来优化求解目标函数。
The objective function was established based on the maximum likelihood rule, which was solved by nonlinear conjugate gradient method.
在计算方法上，采用共轭梯度法。
The conjugate gradient method is employed in developing the algorithm.
将共轭梯度法引入蒙特卡洛随机有限元法，建立基于多项式预处理共轭梯度法的蒙特卡洛随机有限元方法。
An improved MonteCarlo stochastic FEM based on polynomial preconditioners is established through introduction of the conjugate gradients method into the traditional MonteCarlo stochastic FEM.
本文对该方法实际应用的有效性进行了分析和说明，并利用共轭梯度迭代技术实现了垂直有限线源三维电阻率反演。
This paper analyzes the applied effect of this method, then solves the vertical finite line source 3d resistivity inversion by using conjugate gradient relaxation.
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 inverse problem is solved using conjugate gradient method of minimization based on discrete ordinates method of radiative transfer equation.
在求解过程中应用共轭梯度法(CGM)和快速傅立叶变换(FFT)相结合的方法降低所需计算机内存和CPU时间。
The conjugate gradient method (CGM) and fast Fourier transform (FFT) technique are used to reduce the necessary memory and CPU time.
本文根据常微分方程参数反问题的数学理论，将正交化方法同有限差分法结合用于确定水质模型参数，并与正则化方法、最速下降法和共轭梯度法作了比较。
The comparison of the calculation results show that orthogonal rule method is fast, simple and reliable, and is applicable to the calculation of the water quality modeling parameters.
基于空间域共轭梯度算法的盲目图像复原方法由于在复原过程中追求了充分平滑，使得复原图像中的边缘细节信息有所损失。
The restored image obtained by using the space domain conjugate gradient algorithm is too smooth and loses some information about the edge detail.
数值效果显示在数值结果差不多的情况下我们的方法在计算时间上比信赖域-截断共轭梯度法有优越性。
Numerical results demonstrate that our approach is effective, by noting that the computation time is largely shortened in comparison with the trust-truncate CG method.
比较传统的最小二乘反演方法，利用共轭梯度的电阻率三维最小构造反演显示了更好的效果。
The 3-d resistivity inversion for minimum stricture using conjugate gradients shows good results as compared with traditional inversion method of least squares.
约束最优化方法包括梯度法、共轭方向法、牛顿法和拟牛顿法。
Unconstrained optimization methods include gradient, conjugate direction, Newton, and quasi-Newton methods.
第二章，我们考虑用CGE方法(即带早停止准则的共轭梯度法)求解超解像度图像重构问题。
In Chapter 2, we consider using CGE method (i. e. CG with early stop criterion) to solve the super-resolution image reconstruction problem.
第二章，我们考虑用CGE方法(即带早停止准则的共轭梯度法)求解超解像度图像重构问题。
In Chapter 2, we consider using CGE method (i. e. CG with early stop criterion) to solve the super-resolution image reconstruction problem.
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