查询词典 strictly convex function

Let G be the domain whose inverse image is the cross section of u definedin (H1) where the mapping is affine,g and ψ are smooth functions and g＞0,thenthere is a unique smooth convex-monotone function which satisfies the followingproblem 〓Furthermore,if 〓 where C is a constant,ψis an affine function,〓 is astrictly interior sub-domain of G in the sense of"parabolic distance",then

若G为按（H1）中定义的u的截影经仿射变换而得的区域，g和〓为光滑函数且〓，则〓存在惟一的凸单调光滑解。若〓常数，〓仿射函数，〓为G在"抛物距离"下的严格内子域，则

The composite nonsmooth optimization problem is defined as follows:〓where h is a convex function defined on〓and is bounded from below,and〓〓is a mapping from〓to〓and〓are twicecontinuously differentiable function on〓.

复合NDO问题被定义如下：〓这里h是一个定义在〓上的凸函数，并且有下界，〓，〓是一个从〓到〓上的映照。

Assume that the transaction cost funaction is a convex function and the tax function is a concave funcatioh.

我们假设交易费用是交易金额的一个凸函数，而缴纳的税费是其收入的一个凹函数。

Based on the higher mathematics method proved inequalities are summarized, and the proposed using the function extreme value and the monotonicity and concave and convex function sex, and mean value theorem, Taylor formula, integral these common higher mathematics method, combining with concrete examples of each kind of method to solve the problems for type, and the key problem of the specific steps, and points out that the inequality proof of higher mathematics method used properly, improve the difficult easy to ability to solve problems.

本文对不等式证明中的高等数学方法作了归纳总结，提出了利用函数的单调性，极值与最值，函数凹凸性，中值定理，泰勒公式，积分这些常用的高等数学方法，并结合具体实例阐述了每一种方法的适用类型、解决问题的关键和证明问题的具体步骤，指出在不等式证明中恰当地运用高等数学方法可以化难为易，提高解题能力。

The experimental results show that for most continuous optimization problems, the strategy of concave function gains an advantage over the linear strategy, while the linear strategy outperforms strategy of convex function with the identical initial and final weights.

试验结果表明，对于多数连续优化问题，在初始权值和最终权值相同的情况下，凹函数递减策略优于线性策略，而线性策略优于凸函数策略，凹函数递减策略能够在不影响收敛精度的情况下较大幅度地提高粒子群算法的收敛速度。

In this paper, the computation of original likelihood function is transformed into the optimal problem of its low bound through the conjugate representation of the convex function, and a additional parameter is introduced to control the smoothing degree of low bound, and so the performance of local optimal solution can be improved.

我们利用凸泛函的对偶性，将原似然函数的复杂计算问题转化为对其下界函数的优化问题，从而降低学习算法的复杂性；并通过引入一个参数来控制下界函数的光滑程度来改善局部最优解的性能；指出了传统的期望最大化算法(Expectation Maximization Algorithm)是变分学习算法的特殊情况。

This paper presents a new algorithm for feed forward neural networks based on a new optimal target function constructed according to Young inequality in the conjugate of convex function.

提出的算法是利用凸函数共轭性质中的Young不等式构造优化目标函数，这个优化目标函数对于权值和隐层输出来说为凸函数，不存在局部最小。

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

But in our method, the reference function value of the iteration point is defined by a special weighted average, i.e., a convex combination of all previous function values.

而在此算法中，迭代点的参考函数值为一特殊的加权平均值，即前面所有点函数值的凸组合。

Convex function is an significant type of function.

凸函数是一类重要的函数。

But Severus escaped the hands of those that Julianus had sent to murder him and sent a letter to the praetorian guard, giving them the signal either to desert Julianus or to kill him.

赛维鲁总算逃过了尤利阿努斯派来的杀手，并写了一封信给罗马的禁卫军，向他们发出信号，要么抛弃尤利阿努斯，要么干掉他。他们立即服从了。

This text is in terms of this of " human nature ", it is under the influence of western literature human nature thought to probe into, awakening in human nature of novel works and all sorts of limitations that affectionate The school of Mandarin Duck and butterfly.

本文便是从"人性"这一角度，探讨在西方文学人性思想的影响下，清末民初鸳鸯蝴蝶派的言情、哀情小说作品在人性方面的觉醒与种种局限。