查询词典 prove

Simulation results prove that the proposed model is not only effective, but also converged quickly.

仿真结果证明了提出的模型不仅准确有效，而且收敛速度快。

We prove, under some mild assumptions, the local convergence theorem for this class of dual algorithms and present the error bound for approximate solutions.

在适当的假设条件下，证明了该类算法的局部收敛性质，并给出近似解的误差界。

In this thesis, we firstly introduce several class of discrete-time neural network models and the research progress of the neural networks. By Schauder fixed-point principle we prove the existence of an equilibrium (i.e. a fixed point) of a discrete-time neural network with generalized input-output function and by using the converse theorem of Lyapunov function we study the uniformly asymptotical stability of equilibrium in this discrete-time neural network with variable weight and give some sufficient conditions that guarantee the stability of it.

本文首先介绍了几类离散神经网络模型的由来及其研究概况，利用Schauder不动点原理证明了一类具有广义输入输出函数的离散神经网络模型平衡点的存在性，利用Lyapunov函数逆定理给出了这类离散神经网络模型在时变权值下的一致渐近稳定性的充分条件。

If the measures in your experiment show other units, appropriate conversion tables for different systems may prove to be very useful.

如果你实验中所使用的测量工具显示的是其它测量单位，那麼适当的单位换算表格可能会非常有用。

Experimental results prove that the control method of this converter is simple,reliable an...

实验结果表明，该变换器的控制方法简单、可靠和通用。

Experimental results prove that the control method of this converter is simple, reliable and general.

实验结果表明，该变换器的控制方法简单、可靠和通用。

Second, we prove that consensus value of continuous time-invariant systems converges globally asymptotically to the convex combination of initial states, thus, determining the consensus value of the non-balanced topology.

对于多智能体网络连续系统，该系统的一致平衡点最终收敛于初始状态的凸组合，本文最终确定了非平衡拓扑结构的一致平衡点。

Then for general convex programming problem with linear constraints, we developed affine scaling algorithm and prove its convergences.

接着我们对一般的线性约束下的凸规划问题，给出了相应的仿射尺度算法，并证明了算法的收敛性。

Then use it to prove a characteric properties of convex set and some other characteric properties.

这些公式能够被看作是各种交集测度的积分公式，它们对于解决几何概率问题是很有用的。

By weakening the premise of the convexity of the objective function required in paper[7], we prove the sufficient desent property and the global convergence with the strong Wolfe line search.

在第二章中，我们参照文献[7]中的方法，提出了一类与HS算法相关的共轭梯度算法，并减弱了文[7]中要求目标函数二阶连续可微且为凸的前提条件，采用强Wolfe线搜索，在较弱的条件下证明了这一类算法具有充分下降性和全局收敛性。

But we don't care about Battlegrounds.

但我们并不在乎沙场中的显露。

Ah! don't mention it, the butcher's shop is a horror.

啊！不用提了。提到肉，真是糟透了。