查询词典 gradient

During the period of dry, raw material is effected by stirring-up rake with gradient and hot air, it can be moved and passed through the dry region and to star valve and then discharge the finished product.

在干燥过程中，物料在带有倾斜度的抄板和热气流的作用下，可调控地运动至干燥机另一段星型卸料阀排出成品。

Then, in a second interval, the voltage is raised to a second voltage no less than the starting voltage and with an absolute gradient smaller than that for the voltage rise in the first interval.

然后，在第二区间中，电压上升至不小于启动电压的第二电压，并且电压上升的绝对斜率小于在第一区间中电压上升的绝对斜率。

An on-line blind source separation algorithm of non-stationary mixed signals is presented. The algorithm uses the multiple time-delayed decorrelation and natural gradient rule to obtain the stationary point of the cost function, only a small number of observed samples is needed to minimize the Frobenius norm of the correlation matrices, so the computing cost is low and continuous separation calculation could be realized by on-line operation.

利用一种基于多时延解相关准则的代价函数和自然梯度原则，分别推导出非平稳信号在瞬态线性混合及卷积混合情况下的在线盲分离算法，仅通过对有限个时延样本的相关矩阵进行Frobenius范数最小化运算得到分离矩阵，计算工作量小，无需对样本进行分块处理，可实现对信号的连续跟踪操作。

With the idea of smoothing Newton method, we propose a new class of smoothing Newton methods for the nonlinear complementarity problem based on a class of special functions. In this paper, complementarity problem is converted into a series of smoothing nonlinear equations and a modified smoothing Newton algorithm is used to solve the equations. We use Newton direction and Gradient direction together in the algorithm which guarantees that our method is globally convergent. Also using another smoothing function, we reformulate the generalized nonlinear complementarity problems defined on a polyhedral cone as a system of smoothing equations and a smooth unconstrained optimization problem. Theoretical results that relate the stationary points of the merit function to the solution of the generalized nonlinear complementarity problems are presented, we use the modified smoothing Newton algorithm in generalized nonlinear complementarity problems, under mild hypothesis, a global convergence is proved.

本文一方面基于现有的各种光滑Newton法的思想和半光滑理论，利用著名的F-B互补函数的光滑形式，首先将互补问题的求解转化为求解一系列光滑的非线性方程组，然后给出了一种修正的光滑Newton法，该方法不仅放宽对函数F的要求，在Newton方程不可解时引入初始效益函数的最速下降方向，而且光滑因子的选择也比较简单可行，同时在适当的条件下，证明了其算法具有全局收敛性；另一方面，借助另一种F-B光滑函数，将多面体锥上的广义互补问题转化为一种光滑形式，讨论了优化问题的稳定点与广义非线性互补问题的解之间的理论关系，并将这种修正的光滑Newton法用于求解广义非线性互补问题中，在适当的条件下，该算法同样具有全局收敛性。

Steepest gradient descent method had been mostly used in the iteration process of the error energy function during conventional programming problems.

传统的规划问题中，一般使用最陡梯度算法进行误差能量函数的迭代过程。

The mixed method raise the convergent rate of the conjugate gradient method, and solve the problem which the steepest descent method can not solve in the condition with badly characteristics for the objective function.

混合算法既提高了共轭梯度算法的收敛速度，又解决了目标函数"性态不优"时，最速下降法难以求解的问题。

Qinan fault step belt has undergone multiple thermal events with higher paleo-temperature gradient and hydrothermal fluid flow.

研究结果表明，歧南断阶带经历过多期复杂的热事件，古地温梯度明显高于现今地温梯度，热流体活动强烈。

Then, an online optimization algorithm that combines policy gradient estimation by learning and stochastic approximation is derived.

利用此模型的动态结构特性，结合在线学习估计梯度与随机逼近改进策略，提出适应带宽配置在线优化算法。

Then by utilizing the features of this model an online optimization algorithm that combines policy gradient estimation and stochastic approximation is derived.

利用此模型的动态结构特性，结合在线学习估计梯度与随机逼近改进策略，提出动态电源管理策略的在线优化算法。

Genetic algorithms ; inverse design ; stochastic approximation ; gradient

遗传算法；反设计；随机逼近；梯度

The dissecting of samples in group2 were difficult. The root of pulmonary artery and ascending aorta failed to be unfolded because fibrous tissue was tough, right and left fibrous trigone were too firm to be solved by hand. Cardiac muscle fibers couldn't be stripped along myofibrillar trajectory since they were prone to break because of their friability.

组2的心脏解剖困难，表现为纤维组织坚韧，游离肺动脉非常困难；徒手无法松解左、右纤维三角，肺动脉和主动脉根部的游离非常困难；心肌纤维坚硬、质脆，解剖时容易断离成碎块，无法沿纤维走行方向剥离。

We have battled against the odds in a province that has become increasingly violent.

我们对在一个争夺日益激烈省的可能性。