Modalities in linear logic weaker than the exponential “of course”: Algebraic and relational semantics

We present a semantic study of a family of modal intuitionistic linear systems, providing various logics with both an algebraic semantics and a relational semantics, to obtain completeness results. We call modality a unary operator on formulas which satisfies only one rale (regularity), and we consider any subsetW of a list of axioms which defines the exponential of course of linear logic. We define an algebraic semantics by interpreting the modality as a unary operation on an IL-algebra. Then we introduce a relational semantics based on pretopologies with an additional binary relationr between information states. The interpretation of is defined in a suitable way, which differs from the traditional one in classical modal logic. We prove that such models provide a complete semantics for our minimal modal system, as well as, by requiring the suitable conditions onr (in the spirit of correspondence theory), for any of its extensions axiomatized by any subsetW as above. We also prove an embedding theorem for modal IL-algebras into complete ones and, after introducing the notion of general frame, we apply it to obtain a duality between general frames and modal IL-algebras.     

Confidence regions of two-stage stochastic linear complementarity problems

Two-stage stochastic linear complementarity problems (TSLCP) model a large class of equilibrium problems subject to data uncertainty, and are closely related to two-stage stochastic optimization problems. The sample average approximation (SAA) method is one of the basic approaches for solving TSLCP and the consistency of the SAA solutions has been well studied. This paper focuses on building confidence regions of the solution to TSLCP when SAA is implemented. We first establish the error-bound condition of TSLCP and then build the asymptotic and nonasymptotic confidence regions of the solutions to TSLCP by error-bound approach, which is to combine the error-bound condition with central limit theory, empirical likelihood theory, and large deviation theory.     

Absolute Stability of Nonlinear Systems with Two Additive Time-varying Delay Components

In this paper, we present a new sufficient condition for absolute stability of Lure system with two additive time-varying delay components. This criterion is expressed as a set of linear matrix inequalities (LMIs), which can be readily tested by using standard numerical software. We use this new criterion to stabilize a class of nonlinear time-delay systems. Some numerical examples are given to illustrate the applicability of the results using standard numerical software.     

Stabilizing switching design for switched linear systems: A state-feedback path-wise switching approach

This paper addresses the problem of switching stabilization for discrete-time switched linear systems. Based on the abstraction-aggregation methodology, we propose a state-feedback path-wise switching law, which is a state-feedback concatenation from a finite set of switching paths each defined over a finite time interval. We prove that the set of state-feedback path-wise switching laws is universal in the sense that any stabilizable switched linear system admits a stabilizing switching law in this set. We further develop a computational procedure to calculate a stabilizing switching law in the set.     

Stable local dimensionality reduction approaches

Dimensionality reduction is a big challenge in many areas. A large number of local approaches, stemming from statistics or geometry, have been developed. However, in practice these local approaches are often in lack of robustness, since in contrast to maximum variance unfolding (MVU), which explicitly unfolds the manifold, they merely characterize local geometry structure. Moreover, the eigenproblems that they encounter, are hard to solve. We propose a unified framework that explicitly unfolds the manifold and reformulate local approaches as the semi-definite programs instead of the above-mentioned eigenproblems. Three well-known algorithms, locally linear embedding (LLE), laplacian eigenmaps (LE) and local tangent space alignment (LTSA) are reinterpreted and improved within this framework. Several experiments are presented to demonstrate the potential of our framework and the improvements of these local algorithms.     

一类混沌序列线性复杂度的分析

针对传统密码学中由线性移位寄存器生成的序列在统计特性上的不足,提出一种基于混沌的序列密码生成方法,并在有限精度实现时引入Legendre扰动序列使得输出具有良好的统计特性。用B-M算法对其进行线性复杂度分析,并与等效的线性反馈移位寄存器的复杂度进行比较,结果显示该混沌序列具有良好的非线性特性,保密性好且软件实现简单。     

HTML表格向XML的智能转换

XML已经成为处理与管理信息的标准格式,而HTML表格被广泛应用于Web。为了充分利用与管理HTML表格信息,需要将HTML表格转换成XML。提出一种有效的处理方法,该方法包含2个部分,即表格识别与结构转换。表格识别通过检查格式、语法及语义的特征将表格提取出来并分割成值域与属性域,使用预设的表格模板分析属性域与值域间的层次结构并将其转换成XML格式。通过 300多个表格的实验表明,所提出的方法要优于传统方法,结果的准确率达86.7%。     

一种改进的步态识别方法

步态识别通过人体走路的姿势来识别人的身份。近年来,步态作为一种生物特征识别技术备受计算机视觉研究者的关注。对某个人的一个步态序列利用动态Viterbi算法得到一个样本姿态序列,对其多个步态样本姿态序列的对应姿态取平均得到这个人的特征姿态序列,对特征姿态采用主成分分析法和线性判别分析法处理特征空间,并用最近邻法进行识别。利用CASIA数据库对本文方法进行验证,取得了较高的识别率,并对体形变化具有较强的鲁棒性。     

TV改进算法及其在人脸识别中的应用

针对传统全变分（TV）模型在测试过程中存在的问题,将弹性网引入TV模型中,采用二次多项式对TV模型所丢弃的人脸低频信息进行光照归一化处理,并提取图像的高频信息,在YaleB图像库中测试其性能,仿真实验结果表明,相对于TV模型,TV＋二次多项式模型能够有效提高图像识别率。