同时，还可使用迭代的预条件双共轭梯度算法进行计算。
An iterative conjugate gradient algorithm is used in all cases.
研制的最小平方共轭梯度算法和奇异值分解法也可进行同样的层析反演。
The least square conjugate gradient and odd values decomposition method also can be used to perform tomographic inversion.
本算法用自适应算法，二次型共轭梯度算法，解前后向预测构成的矩阵方程。
The new algorithm uses the quadratic conjugate gradient algorithm (QCGA) to solve the forward-backward linear prediction matrix equation.
在常规算法的基础上，提出了一种基于变斜率算法与共轭梯度算法的接力逆向传播算法。
An artificial neural network algorithm, based on variable slope BP algorithm and conjugate gradient algorithm, is presented in this paper.
针对闪光照相系统成像信噪比低的特点，提出了正则化预优约束共轭梯度算法(RPCCG)。
Based on the constrained conjugate gradient algorithm, a regularization preconditioned constrained conjugate gradient algorithm (RPCCG) was proposed for image-reconstruction for radiography.
本文对该算法中的线搜索进行了推广，提出了一种新的非线性共轭梯度算法并证明了其全局收敛性。
This paper presents a wide line search and gives a new conjugate gradient method, with global convergence.
在分析电容层析成像基本原理和图像重建算法的基础上，提出一种结合正则化优化修正的共轭梯度算法。
Based on the analysis of basic principle of electrical capacitance tomography and the image reconstruction algorithm, a conjugate gradient algorithm with optimized regularization is proposed.
本研究设计了适用于GPS单点定位计算的BP人工神经网络模型结构，采用共轭梯度算法改善网络的训练速度和精度。
The BP network architecture applied to determine GPS standalone position is designed. Meanwhile, the conjugate gradient algorithm is used to improve the training velocity and accuracy of the network.
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.
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.
将最速下降法与共轭梯度法有机结合起来，构造出一种混合优化算法，并证明其全局收敛性。
Based on the steepest descent method and the conjugate gradient method, a hybrid algorithm is proposed in this paper, and its global convergence is proved.
PCG算法是牛顿法和预优共轭梯度法结合起来解牛顿方程的一种非精确牛顿法。
Newton PCG method is an inexact Newton like method. It is an organic combination of Newton's method and preconditioned conjugate gradient method.
PR共轭梯度法是求解大型无约束优化问题的有效算法之一，但是算法的全局收敛性在理论上一直没有得到解决。
Pr conjugate gradient method is one of the efficient methods for solving large scale unconstrained optimization problems, however, its global convergence has not been solved for a long time.
本文针对传统BP算法存在的两个常见问题进行了讨论，提出了基于步长优化和共轭梯度法的改进BP算法。
This paper discussed two basic problems of conventional BP algorithm. A improved BP algorithm based on step optimum and conjugate gradient was put forword in this paper.
本文介绍一种沿曲线方向线性搜索的算法，这种算法概括了梯度法、共轭梯度法以及它们的改进格式。
This paper introduces a curvilinear line searching technique, which possesses all the meris of the gradient method, the conjugate gradient method and some of their refined types.
利用共轭梯度法的思想，建立相应的迭代算法。
A corresponding iterative method is presented by making use of conjugate gradient method.
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.
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.
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.
共轭梯度法是求解最优化问题的一类有效算法。
Conjugate gradient methods are important iterative methods for solving optimization problems.
提出一种基于非线性共轭梯度法的唯相直接数据域最小二乘算法。
A phase-only direct data domain least square (D3LS) algorithm based on the nonlinear conjugate gradient method was proposed.
网络训练时采用共轭梯度学习算法并对此算法进行了改进，有效的克服了梯度学习算法容易陷入局部极小的缺点。
Moreover, an improved conjugate gradient algorithm is used to train the network and to overcome the shortcoming of easily trapping into local minimum points.
就训练次数与精确度而言，它明显优于共轭梯度法及变学习率的BP算法，适用于系统辨识。
Concerned with the training process and accuracy, the LM algorithm is superior to conjugate gradient algorithm and a variable learning rate back propagation (BP) algorithm.
通过离线的迭代算法生成高精度的样本点来训练神经网络，使用动量法、变学习率法和共轭梯度法提高BP网络的收敛速度。
Methods based on BP neural network and RBF neural network were studied to solve inverse kinematics. The training samples were obtained through off-line numerical method with high precision.
非线性优化技术、分枝定界算法和不完全乔莱斯基分解的预优共轭梯度法是该工作的三个主体部分。
Nonlinear programming techniques, branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.
非线性优化技术、分枝定界算法和不完全乔莱斯基分解的预优共轭梯度法是该工作的三个主体部分。
Nonlinear programming techniques, branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.
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