• 算法计算速度快,计算单调收敛存在振荡现象。

    The method without "surge" has high calculation velocity and monotonic convergence.

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  • 我们算法收敛速率估计,最后还给出了单调收敛定理

    We estimate the convergence rate of this method and give its monotone convergence theorems.

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  • 仿真结果表明采用给出的最优设计具有更好的迭代学习单调收敛性能

    Simulation results show that better monotonic convergence performance is achieved by using the

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  • 数值结果显示方法优越性包括迭代序列单调收敛有限差分解高精度

    The numerical results demonstrate the advantages of the method, including the monotone convergence property of iterative sequences and the high accuracy of the method.

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  • 本文指出矩阵迭代迭代过程中,特征值近似值序列单调收敛的,给出计算实例

    This paper indicated that the sequence of approximate value of eigenvalue is monotone convergent in the iteration process of matrix iteration method. And also gave examples.

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  • 算法相比方法为多点寻优,单调收敛,可获得全局最优解用于长、短期或实时优化调度。

    The algorithm USES a population of points at a time in contrast to the single point approach by traditional optimization methods. The convergence is monotonic and a global solution is obtained.

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  • 本文主要运用具有全局收敛单调迭代求解了一类非线性扩散方程数值

    This paper mainly studies the numerical solution of a class of nonlinear diffusion equations using a monotone iteration method with the global convergence.

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  • 提出一个新的下降方向,在函数单调条件证明算法全局收敛性。

    In this paper, we propose a new descent direction. Under the pseudomonotone of the underlying function, we prove the global convergence of the algorithm.

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  • 导出选择和变异条件平均适应度单调递增并收敛全局优解条件。

    Sufficient condition for monotonous increase of the average fitness converging to the global maximum value is derived.

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  • 为了求解非线性差分格式,本文建立一种加速单调迭代算法给出精确收敛估计。

    To solve the nonlinear finite difference scheme, an accelerated monotone iterative method is presented, and the explicit estimate for the rate of convergence is given.

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  • 利用牛顿方向中心路径方向,获得了求解单调线性互补问题算法证明算法经过多项式次迭代之后收敛到原问题的一个最优解。

    By using Newton direction and centering direction, we establish a feasible interior point algorithm for monotone linear complementarity problem and show that this method is polynomial in complexity.

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  • 改进网络学习效率大范围收敛性,提出网络权值学习的单调方法方法具有牛顿相同的二阶收敛性。

    To improve the learning efficiency and global convergence we present the monotone homotopy method, which has the same convergence as the Newton's method, to train the weights of the network.

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  • 本文提出一类求解无约束优化问题单调曲线搜索方法条件下证明了收敛

    This paper presents a non-monotone curve search method for unconstrained optimization problems and proves its convergence under some mild conditions.

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  • 给出一种新的单调信赖方法证明算法的全局收敛线性收敛性,最后给出了数值结果

    A new nonmonotonic trust region method is given in this paper. And its global convergence and superlinear convergence are proved. Numerical results are given.

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  • 应用单调有界定证明一类数列收敛过程,一般高等数学和数学分析教材中,处理思路方法不易想到或过程较为繁琐

    In many current textbook, the monotone bounded theorem is used to the proof the convergence of a kind of but this method is uneasy to series, understand.

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  • 本文研究系数单调算子椭圆型微分方程,得到了解的梯度的几乎处处收敛

    In this paper, we study the elliptic partial differential Cquation whose coefficients are strongly monotony operators, and obtain the everywhere convergence of the gradients of solutions.

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  • 算法具有快速收敛保证每步迭代模型概率单调增的优点

    Its strength lies in fast convergence and monotonous improvement of the likelihood probability.

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  • 定理7.1。如果一个数列单调并且界,这个数列才能收敛

    THEOREM 7.1. A monotonic sequence converges if and only if it is bounded.

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  • 我们乐意处理单调递增数列单调递减数列,因为特别容易确定数列的收敛发散

    Monotonic sequences are pleasant to work with because their convergence or divergence is particularly easy to determine .

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  • 此文对“单调数列收敛条件单调,有界的证明方法加以归纳就两个条件的关系一类特殊情况加以讨论,得出结论。

    The essay is a summary concerning how to demonstrate the two prerequisites monotone and bounds in "monotonous and boundary number line necessarily converge."

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  • 给出求解单调变分不等式问题一个近似邻近点算法不需要任何中间步骤的条件下证明算法的收敛

    This paper presents a approximate proximal algorithm finding the zero of a maximal monotone operator in Hilbert space, whose error criterion is weaker than that in the literatures.

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  • 给出求解单调变分不等式问题一个近似邻近点算法不需要任何中间步骤的条件下证明算法的收敛

    This paper presents a approximate proximal algorithm finding the zero of a maximal monotone operator in Hilbert space, whose error criterion is weaker than that in the literatures.

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