conjugate gradient
通过迭代逼近最优解。
常用释义
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基本释义
- 共轭梯度法：一种用于求解线性方程组的迭代算法，通过迭代逼近最优解。
例句
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1·Conjugate Gradient; Sufficient Descent Property; Convergence.共轭梯度，充分下降，收敛性。
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2·The conjugate gradient method was selected as the inversion kernel.该方法选取共轭梯度反演算法为拟三维反演的核心。
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3·The conjugate gradient method is employed in developing the algorithm.在计算方法上，采用共轭梯度法。
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4·A corresponding iterative method is presented by making use of conjugate gradient method.利用共轭梯度法的思想，建立相应的迭代算法。
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5·For this theory, it is better than the traditional fixed damping conjugate gradient method.从理论上讲，它要优于传统的固定阻尼共轭梯度法。
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6·Conjugate gradient methods are important iterative methods for solving optimization problems.共轭梯度法是求解最优化问题的一类有效算法。
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7·The parameters of the neural network PID controller are modified on line by the improved conjugate gradient.并用这种改进的共轭梯度法对神经网络PID控制器参数实现在线修正。
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8·In this paper, the relationship of DFP variable metric method and FR conjugate gradient method is investigated.研究了求解无约束极值问题的DFP变尺度法和FR共轭梯度法的关系问题。
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9·The conjugate gradient method is one of the most efficient methods for solving unconstrained optimization problems.共轭梯度法是求解无约束优化问题的一类有效方法。
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10·An incomplete Cholesky-conjugate gradient method is used to solve the pressure equation of two phase bi-dimension model.本文把不完全乔利斯基——共轭斜量解法用于求解二维二相模型的压力方程。