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  • The function is continuously differentiable.

    函数是连续可微分的。

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  • Not all continuous functions are differentiable.

    函数是连续可微分的。

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  • OK, so most of the functions we'll see are differentiable.

    因此大多数我们会遇到的函数都是可微的。

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  • You will see why. It is defined and differentiable in r.

    你们会明白为什么的,它在R上有定义,且是可微的。

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  • The results for differentiable homeomorphism are extended.

    并推广了微分同胚的有关结果。

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  • 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。

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  • And, we say that a function is differentiable if these things exist.

    我们说一个函数是可微的,如果这些偏导数存在。

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  • There is a nodus to design an observer for nonlinear bounded continuous differentiable system.

    对于非线性有界连续可导系统的观察器设计是观察器设计的难点之一。

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  • This article was to offer the method about the complex function's differentiable and holomorphic.

    文章针对被积函数是连续函数、可导函数的定积分不等式提出了几种有效的证明方法。

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  • That means you need your vector field to be continuous and differentiable everywhere on the surface s.

    也就是,向量场是连续的,且在曲面s上处处可微。

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  • In this paper, a decomposability theorem is presented and proved by differentiable manifolds theories.

    本文提出并采用微分流形理论证明智能机器人体系结构可分解性定理。

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  • In this paper, the star-kernel of a quasi-differentiable function in one-dimensional space is studied.

    本文在一维情形下对拟可微函数的星核进行了讨论,证明了拟微分星-有界等价子类的存在性;

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  • In our results, we do not require activation functions to be bounded, differentiable or strictly increasing.

    同已有的结果相比,我们不要求函数有界,可微或严格增加等条件。

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  • In this paper an interval iterative method is given for seeking the global maximum of a second order differentiable function.

    本文就二次可微函数类给出一类求大范围极值的区间迭代方法。

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  • Some Suggestions for executing this method are presented, graphical results of nowhere differentiable continuous function are shown.

    对此,阐明了一些有效的建议,并给出了无处可微连续函数的图示结果。

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  • The linearized procedure for differentiable nonlinear programming problems can be naturally generalized to the quasi differential case.

    可微非线性规划问题的线性化过程可以自然地推广到拟可微的情形。

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  • Because the error transfer function of rough neural network is not differentiable, genetic algorithms are applied for training the network.

    由于粗神经网络的误差传递函数不可微,所以采用遗传算法来训练粗神经网络。

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  • This article was to offer necessary and sufficient condition and application of conjugate differentiable complex function in complex system.

    给出了复形式的复变函数的共轭可微性充要条件的证明及其重要应用。

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  • By very elementary method, it is proved that every continuous differentiable function defined in a perfect set has differentiable extension.

    本文完全用初等的方法证明了完全集上连续可微函数都有可微开拓。

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  • It is also proved as application that any bounded variation function can be seen as a differentiable function beside a set of arbitrary small measure.

    作为应用,证明了任意有界变差函数都与某可微函数在除过测度任意小的集合外重合。

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  • For the learning process, a new kind of empirical risk function is proposed which is differentiable and can be minimized by gradient descent strategy.

    对于参数的学习,提出了一种适用于分类器的可微经验风险函数,该函数能够有效地利用梯度下降法进行最小化。

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  • Every Layer has a simple API: it transforms an input 3d volume to an output 3d volume with some differentiable function that may or may not have parameters.

    每一层都有一个简单的API:用一些含或者不含参数的可导的函数,将输入的三维数据变换为三维的输出数据。

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  • To solve a class of non-differentiable optimization problems, this paper proposed a new method called maximum-entropy particles swarm optimization algorithm.

    针对一类不可微优化问题,本文提出了一个新的算法—极大熵微粒群混合算法。

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  • A type of continuous and Non-differentiable Function is studied, its characteristics and essence are revealed, and its condition of construction is presented.

    对一类连续但不可导函数进行研究,揭示其特点和本质,并给出其构造条件。

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  • The value function turns out to be continuous in the whole plane, and is even continuously differentiable in the interiors of both right and left half planes.

    说明了值函数在整个平面上是连续的,在左右两个半平面的内部还是连续可微的。

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  • Minimax problem is a sort of non-differentiable optimization problem and the entropy function method provides a efficient approach to solve such kind of problems.

    极大极小问题是一类不可微优化问题,熵函数法是求解这类问题的一种有效算法。

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  • Minimax problem is a sort of non-differentiable optimization problem and the entropy function method provides a efficient approach to solve such kind of problems.

    极大极小问题是一类不可微优化问题,熵函数法是求解这类问题的一种有效算法。

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