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.
该文提出一种无约束优化非线性共轭梯度法，证明了精确线性搜索下的全局收敛性。
The paper presents a nonlinear conjugate gradient method for unconstrained optimization problem, and proves its global convergence under exact line searches.
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.
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.
稳定化双共轭梯度法用于求解稀疏线性方程组，可调节参数的修正迭代法用于求解非线性代数方程组。
Linear equations of sparse matrix are solved by Biconjugate Gradients Stabilized Method and nonlinear algebraic equations are solved by parameter-regulated iterative procedures.
梯度法对许多非线性问题均具有较好的性能，计算目标函数可以使用新的共轭变量法，有望显著提高寻优效率。
Generally, to nonlinear problem, gradient-based method is faster than simple method, and may improve efficiency due to using conjugate variables to calculate object function value.
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.
另一方面，采用传统迭代子和共轭梯度法作为光滑子，我们证明了瀑布型多重网格法对一、二维非线性椭圆边值问题，在能量范数下，均可获得最优收敛阶。
Onthe other hand, with traditional iterations and the conjugate gradient(CG) as smoothers, we can show the optimal convergence rate of the cascadic method in energy norm for 1-D and 2-D cases.
另一方面，采用传统迭代子和共轭梯度法作为光滑子，我们证明了瀑布型多重网格法对一、二维非线性椭圆边值问题，在能量范数下，均可获得最优收敛阶。
Onthe other hand, with traditional iterations and the conjugate gradient(CG) as smoothers, we can show the optimal convergence rate of the cascadic method in energy norm for 1-D and 2-D cases.
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