可微的

基本解释 (translations)

differentiable

与可微的相关的网络例句 [注：此内容来源于网络，仅供参考]

In this paper, we present a nonmonotone line search model algorithm for the nonsmooth composite minimization problems minhf(x, where each f: Rn→Rn is a locally Lipschitzian function, and h: Rn→R is a continuously differentiable convex function.

1引言考虑下面的复合极小化问题minF=hf(x，(1 。1)二〔丫其中f：R"一R"是局部Lipschitz函数，h：Rn一R是下有界的连续可微的凸函数。对于问题(l 。1)，QIL、袁亚湘和孙文瑜等z1一

Every polynomial is differentiable, and so is every rational .

每个多项式都是可微的，而每个有理函数也是如此。

Not all continuous functions are differentiable.

不是所有的连续函数都是可微的。

Using Bruck抯 Lemma [2], Passty [7] extended to the results of [4,5] to a uniformly convex Banach space with a Frechet differentiable norm.

随后，Passty［7］又利用Bruck引理[2]将[4][5]的结果推广到具有范数Frechet可微的一致凸Banach空间中。

Polynomial smooth techniques are applied to SVM model and replace x+ by a very accurate smooth approximation that is Hermite Interpolation polynomial,thus the undifferential model is converted into a differential model.The deduction procedure of Hermite Interpolation polynomial smoothing x+ is extended.

三次Hermite插值多项式光滑的支持向量机模型采用的是一种多项式光滑技术，用三次Hermite插值多项式代替单变量函数x+，将原来不可微的模型变为可微的模型，并且给出了三次Hermite插值多项式光滑化单变量函数x+的推导过程。

At first, A Lagrangian function of the problem is introduced.

通过引入该问题的Lagrange函数，建立一个可微的价值函数。

In this paper,continuous differentiable conditios of output response functions of Hopfied neural networks in usual papers is reduced to Lipschitz condition.

因此，本文将通常论文中Hopfield神经网络的输出响应函数连续可微的假设削弱为满足L ipschitz条件。

Using normal distribution transform probability model to represent a laser range scan.Not need features corresponded,but transform the discrete scan date to the piecewise continuous and differentiable probability density function,and using Newton's algorithm to optimize scan matching,so can build the 2D global map.

利用正态分布转换概率模型来表示激光扫描，不需利用特征对应，而是通过将扫描得到的离散数据点转换成分段连续可微的概率密度函数，并利用牛顿优化算法来进行扫描匹配，从而建立2维全局地图。

For most matrix of A,the linear diffrentiable equations with quasi-periodic finitely differentiable coefficients are reducible.

证明了对大多数的矩阵A，一类系数为有限次可微的拟周期线性常微分方程组是可约的。

In Chapter 4, a new algorithm for the solution of nonlinear complementarity problems is developed.

第四章对求解互补问题的可微的无约束优化法作了研究。

与可微的相关的网络解释 [注：此内容来源于网络，仅供参考]

continuously differentiable：连续可微的

continuously deformable 可连续形变的 | continuously differentiable 连续可微的 | continuously operated 持续工啄

derivability：可微性

depth line 深度线 | derivability 可微性 | derivable 可微的

derivable：可微的

derivability 可微性 | derivable 可微的 | derivate 导出数

differentiability：可微性,可微分性

different species | 异类 | differentiability | 可微性,可微分性 | differentiable | 可微分的

differentiable function：可微函数

differentiable 可微的 | differentiable function 可微函数 | differentiable manifold of class c c类微分廖

differentiable：可微的

differentiability 可微性 | differentiable 可微的 | differentiable function 可微函数

totally differentiable：完全可微的

完全局部环|complete local ring | 完全可微的|totally differentiable | 完全可约表示|completely reducible representation

right hand differentiable：右方可微的

right hand derivative 右方导数 | right hand differentiable 右方可微的 | right hand half open interval 右方半开区间

right side differentiable：右方可微的

right side derivative 右方导数 | right side differentiable 右方可微的 | right tensor product 右张量乘积

termwise differentiable：逐项可微的

terms-of-trade effect 贸易条件效果 | termwise differentiable 逐项可微的 | termwise differentiation 逐项微分