线性收敛性的英文

• linear convergence

• "线性"英文翻译    linear; linearity
• "收敛"英文翻译    weaken or disappear
• "性"英文翻译    nature; character; dispositi ...
• "超线性收敛性" 英文翻译 :    superlinear convergence
• "超线性收敛" 英文翻译 :    superlinear convergence
• "线性收敛" 英文翻译 :    linear convergence
• "收敛性" 英文翻译 :    astringency; astringent nature; convergence; convergency
• "收敛药,收敛性的" 英文翻译 :    adstringens
• "半收敛性的" 英文翻译 :    gubastringent
• "传输收敛性" 英文翻译 :    physical media specific-transmission convergence
• "殆必收敛性" 英文翻译 :    almost sure convergence
• "单调收敛性" 英文翻译 :    monotonic convergence
• "二阶收敛性" 英文翻译 :    quadratic convergence
• "级数收敛性" 英文翻译 :    series convergence
• "绝对收敛性" 英文翻译 :    absolute convergence
• "偶然收敛性" 英文翻译 :    accidental convergence
• "收敛性的" 英文翻译 :    astrictive; astringent; constringent; styptic
• "收敛性地" 英文翻译 :    astringently
• "收敛性加速" 英文翻译 :    konvergenzbeschleunigung convergence acceleration
• "收敛性检定" 英文翻译 :    test for convergence
• "收敛性检验" 英文翻译 :    test of convergence
• "收敛性判别" 英文翻译 :    konvergenzkriterium convergence criterion
• "收敛性判定" 英文翻译 :    convergence test
• "收敛性子层" 英文翻译 :    cs convergence sublayer
• "算法收敛性" 英文翻译 :    algorithm convergence

• We also show that the unit steplength is essentially accepted
  并证明算法的全局收敛性和超线性收敛性。
• A class of global convergent memory gradient methods and its linear convergence rate
  一类全局收敛的记忆梯度法及其线性收敛性
• Under mild conditions , we prove the global and superlinear convergence of the method
  在较弱的条件下，得到了算法的全局收敛性及其超线性收敛性。
• Using the comparison principle , it is proved that the proposed method is of superlinear convergence
  利用比较原理，间接证明该算法是一种具有超线性收敛性的近似牛顿法。
• Moreover , we show that if the second order sufficient conditions holds at a solution of the problem , then the method is 2 - step superlinearly convergent
  而且，我们证明：若在问题的解处二阶充分条件成立，则相应的sqp算法具有2步超线性收敛性。
• Lc1 unconstrained optimization problem was discussed in the second chapter , giving a new trust region method and proving its global convergence and superlinear convergence under some mild conditions
  给出了一个新的信赖域算法，并在一定的条件下证明了算法的全局收敛性和局部超线性收敛性。
• Under mild conditions , we prove that the proposed method is globally convergent . moreover , we show that after finite iterations , the unit step is always accepted , and the method locally reduces to the modified bfgs method
  在较弱的条件下，我们证明所提出的方法具有全局收敛性，此外，本文证明在有限次迭代后，单位步长总是可接受的，因此，算法还原为mbfgs法，从而这种方法具有局部超线性收敛性。
• It exploits the structured of the hessian matrix of the objective function sufficiently . an attractive property of the structured bfgs method is its local superlinear / quadratic convergence property for the nonzero / zero residual problems . the local convergence of the structured bfgs method has been well established
  它们充分利用了目标函数的hesse矩阵的结构以提高算法的效率，该算法的显著优点是对于零残量问题具有二阶收敛性而对于非零残量问题具有超线性收敛性。
• In the third chapter we discuss lc1 constrained optimization problem . to solve it , we turn it into nonsmooth equations , utilizing inexact theory we give an inexact generalized newton ' s method and under some mild conditions we prove that it is global convergence and superlinear convergence
  首先将其约束问题的求解转化为非光滑方程组的求解，然后利用不完全求解理论给出了一个非精确的广义牛顿算法，在一定的条件下证明了算法的全局收敛性和局部超线性收敛性并给出了lc ~ 1非线性约束问题的收敛性条件。
• Because three systems of equations solved at each iteration have the same coefficients , so the ammount of computation are less than that of the existing sqp algorithms . under some common conditions ( such as the second order sufficient condition ) which are used in some references , we prove that the algorithm possesses not only global convergence , but also strong convergence and superlinear convergence
  该算法在每次迭代时所需解的三个线性方程组具有相同的系数，因此计算量要比现有的sqp方法有所减少；在与一些文献平行的假设条件(如二阶充分条件)下，论文证明了算法不仅具有全局收敛性，而且还具有强收敛性和超线性收敛性