Input saturation and global stabilization of nonlinear systems viastate and output feedback

For multi-input multi-output nonlinear systems whose free dynamics are Lyapunov stable, the author shows how the problem of global stabilization via dynamic output feedback can be solved by using the technique of input saturation. The power of this technique is also illustrated by solving the problem of global stabilization via bounded state feedback for affine nonlinear systems with stable unforced dynamics. Analogous results are established for discrete-time nonlinear systems     

两种具有电双稳态的全有机络合物

首次发现两种在室温下即具有电双稳态的全有机（有机-有机）络合物，分别称为MCA＋TCNQ和BBDN＋TCNQ。它们可在真空中制备成薄膜，在数伏电压的作用下，从高电阻至低电阻的跃迁时间小于100ns，因此可作为一次写入的存储器材料。根据我国目前最小刻线宽度的水平，可望在1．6cm2的SiO2平面上做出64Mb的存储器。     

A singular loop transformation framework based on non-singular matrices

In this paper, we discuss a loop transformation framework that is based on integer non-singular matrices. The transformations included in this framework are called Λ-transformations and include permutation, skewing and reversal, as well as a transformation calledloop scaling. This framework is more general than existing ones; however, it is also more difficult to generate code in our framework. This paper shows how integer lattice theory can be used to generate efficient code. An added advantage of our framework over existing ones is that there is a simple completion algorithm which, given a partial transformation matrix, produces a full transformation matrix that satisfies all dependences. This completion procedure has applications in parallelization and in the generation of code for NUMA machines. This work was supported by the Cornell Theory Center, NSF Presidential Young Investigator award #CCR-8958543. by NSF Grant #CCR-9008526, and by a grant from the Hewlett-Packard Company.     

Negative effects of sufficiently small initial weights on back-propagation neural networks

In the training of feedforward neural networks,it is usually suggested that the initial weights should be small in magnitude in order to prevent premature saturation.The aim of this paper is to point out the other side of the story:In some cases,the gradient of the error functions is zero not only for infinitely large weights but also for zero weights.Slow convergence in the beginning of the training procedure is often the result of sufficiently small initial weights.Therefore,we suggest that,in these cases,the initial values of the weights should be neither too large,nor too small.For instance,a typical range of choices of the initial weights might be something like(0.4,0.1) ∪(0.1,0.4),rather than(0.1,0.1) as suggested by the usual strategy.Our theory that medium size weights should be used has also been extended to a few commonly used transfer functions and error functions.Numerical experiments are carried out to support our theoretical findings.     

大型数据集的多维变量关联性挖掘

为了探索多维数据集中各变量之间的关系,特别是非函数关系,对数据集所在的n维立方体的各个维度进行划分,在得到的n维网格中定义自然概率密度函数,以此得到数据集在特定划分下的互信息值。对所有的划分取互信息最大值,正态化后即为所定义的特征张量的一项,取特征张量在给定最大网格数下的最大项的值定义为MIC,它度量了多维变量间的关联程度。     

高职计算机专业校内生产性实训教学模式研究

校内生产性实训是培养具有高素质技能人才的重要手段与教学形式．其对于提升高职教育内涵、服务经济与社会发展具有重要的意义。分析当前高职院校校内生产性实训的现状、特点与类型,在笔者所在学院的实践基础上,构建计算机专业校内生产性实训的“教、学、生产一体化”的教学模式．     

三网融合对测评技术的影响

从宏观上说明了三网融合[1]存在的安全问题,另外详细地介绍了三网融合用到的新技术所产生的安全风险,以及在安全评测中关注的重点问题和实施策略,最后汇总了测评实施过程中的要点。     

欠驱动机器人控制策略综述

欠驱动机器人是指独立控制输人量少于系统自由度的一类机器人,具有重量轻、成本低、能耗低等众多优点,目前已引起学者们的广泛关注,介绍了欠驱动机器人控制器设计的六类策略,分析了各类策略的应用及效果,如何将鲁棒控制与其它控制策略相结合,开发出更实用、性能更优越的控制策略,有待于进一步研究.