查询词典 radon nikodym theorem

In view of the fuzzy characteristics of real world, fuzzy set theory and statistics with vague data are combined to generalize key theorem and bounds on rate of uniform convergence of learning processes as the base of statistical learning theory in this thesis.

摘要考虑到现实世界的模糊性，本文结合模糊集理论和模糊统计学的知识，对作为统计学习理论基础的关键定理和学习过程一致收敛速度的界进行推广，给出了模糊学习理论的关键定理和一致收敛速度的界。

In view of the uncertainty of the real world, trust theory and statistical learning theory are combined to generalize the key theorem and the bounds on the rate of uniform convergence of learning theory. This paper mainly investigates the basic problems of statistical learning theory with rough samples.

考虑到现实世界的不确定性，本文结合统计学习理论和信赖理论的知识，讨论了基于粗糙样本的统计学习理论的基本问题，对作为统计学习理论基础的关键定理和学习过程一致收敛速度的界进行了推广。

With a view of this, we propose the key theorem and discuss the bounds on the rate of uniform convergence of learning processes based on ERM principle when samples are corrupted by zero-expect noise.

基于此种考虑，本文提出了样本受零均值噪声影响下的学习理论的关键定理，并讨论了零均值噪声样本下的学习过程一致收敛速度的界。

At first, using fixed point theorem, we establish the sufficient conditions which guarantee the existence, uniqueness, uniform stability of periodic solutions for the equations.

首先，我们利用不动点定理，建立了保证该类方程周期解的存在性、唯一性及一致稳定性的充分条件。

Using the Lyapunov-Krasovskii functional stability theorem, it is proved that the designed controller makes the closed-loop system semi-globally uniformly ultimate bounded.

所提出的控制器设计思路可以推广到更高阶的多重时滞非线性系统。

The existence of pointwise robust convergent algorithm and uniformly robust convergence is next investigated. We propose an optimal l〓 robustness synthesis method for structured perturbations system by taking advantage of the famous Small Gain Theorem.

证明了最优l〓辨识算法的存在性；证明了黑箱辨识存在辨识算法使全局误差收敛于有界区间；提出并证明了逐点鲁棒收敛算法的存在性；证明了一致鲁棒收敛算法的存在性。

In this paper, the problem of an iterative sequence approximation a common fixed point for nonexpansive non-self mappings is studied in real uniformly convex Banach space, then we obtain a strongly convergence theorem.

在实一致凸Banach空间中，讨论了关于非扩张非自映射序列逼近公共不动点的问题，获得了一个强收敛定理，改进和推广了现有文献的一些相应结果。

The objective of Chapter 2 is to give the weak convergence theorem of S ={T1 :t E G of asymptotically nonexpansive mappings in a uniformly convex Banach space without assuming that X has a Frechet differentiable norm.

本文第二章在G仅要求是一个定向网，X为不具有范数Frechet可微条件的一致凸Banach空间的情况下，给出了一族渐近非扩张映射的弱收敛定理。

This paper,uses the property of being uniformly integrable to truncate the random variable sequences,and under the condition of φx↑,φx2↓,obtain a weak law of large number of martingale difference sequences by the weak convergence theorem.

通过使用一致收敛性对随机变量序列进行截尾，并借助随机变量序列的弱收敛定理，在φ↑，φx2↓的条件下给出了一个鞅差序列的弱大数定律。

Therefore, it is necessary to explain the usage condition of the theorem of uniqueness of solution of elasticity.

为此，需要对弹性力学解的唯一性定理的适用条件适当加以说明。

You can snipe the second and third union leaders from this position.

您可以鹬第二和第三工会领袖从这一立场出发。

Aiming at the currently shortage of XML streams quality detecting, this paper proposes a new forecasting method of XML streams quality by least squares support vector machines, which is used the method of XML keys' vector matrix as windows, and vector product wavelet transform to multilevel decompose and refactor the XML streams series, that can fulfill real-time checking demand of XML quality, and ensure constraint, consist- ency and integrality. For even more adapting net load, it proposes a control strategy by weight and adaptive adjustment to ensure XML streams quality.

针对当前XML数据流质量检测存在的不足，提出构建XML键的矢量矩阵作为窗口，利用矢量积小波变换多级分解与重构XML数据流，再结合最小二乘支持向量机对XML数据流质量进行预测的一种方法，满足XML数据流质量重构时实时检测的要求，保证XML数据的约束性、一致性与完整性；为了更好的适应网络负载，采取加权与自适应窗口调整等调度策略充分保证XML数据流的质量检测。