H ∞ and Robust Control of 2-D Systems in FM Second Model

This paper deals with output feedback stabilization and H control problems for two-dimensional (2-D) discrete linear systems without or with parameter uncertainty. The class of systems under investigation is described by the 2-D local state space Fornasini-Marchesini second model. We aim at designing a dynamical output feedback controller to achieve asymptotic stability and H performance for the 2-D system. It is shown that the design of output feedback controller can be recast into a convex optimization problem characterized by linear matrix inequalities (LMIs). The LMI solution is further extended to solve the robust stabilization problem for 2-D systems subject to norm-bounded uncertainty. The solutions for the H control and robust stabilization are applied to two application examples: thermal process control and robust stabilization of processes in Darboux equation.     

An intelligent adaptive system for the optimal variable selections of R&D and quality supply chains

The cost of research & development (R&D) and quality management are always regarded as two major parts of total cost. The variable performance of R&D and quality design is an important index that will reflect the effectiveness of the cost reduction. This research has attempted to simultaneously vary all of the variables to achieve the global optimum for the optimal variable selections of R&D and quality design. Genetic algorithm (GA) can treat all of the variables for the global search. In this study, fuzzy refinement with orthogonal arrays was effective in improving the performance of the GA, and also showed the benefits of a good chromosome structure on the behavior of GA. It is also proposed the postponement design with temporal concept, to select the effective variables for the cost reduction of R&D and quality management design. The experimental results showed that tempo-postponement design will increase the flexibility and quick response for supply chain management. Hence, this approach can act as a useful guideline for researchers working on the optimization of the key variable selections for R&D and quality model design.     

无线网络安全之802.11i

日前无线网络的安全防护已经逐渐被提上议程,本文首先阐述了传统安全技术,随后重点论述802.11i标准及其相关理论--802.1x认证机制。802.11i标准引入了802.1x认证机制实现身份验证及密钥管理等功能。文章详细描述了802.1x认证机制的实现过程和802.11i标准的安全防护措施,为无线网络安全的各个方面提出了完整的标准措施。     

Visual Studio.NET和Matlab集成应用

分析MATLAB编译器4.x的新特点,提供一种MATLAB7.x与Visual Studio.Net相集成并生成可独立运行应用程序的方法,并对该方法给出具体实现步聚和系统设置。利用该方法,已在工程中取得了成功运用。     

News and notes.

This section of News & Notes provides information on current news from Division 26. Included in this section are Minutes of the 2005 Business Meeting of the Society for the History of Psychology (APA Division 26), New Business, History of Psychology Around the World: The British Psychological Society’s History of Psychology Centre, Psychology on Film: The Prelinger Archives of Ephemeral Films and The Archives of the History of American Psychology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

News and notes.

This section of News & Notes provides the latest information about the Society for the History of Psychology. It contains Division news for the Division 26 of the American Psychological Association Society for the History of Psychology, meeting reports for the Society for the History of Psychology Program at the Convention of the Association for Psychological Science, call for papers, general member news, and reports from the field. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

802.11无线局域网安全与应用研究

分析了WEP加密的原理及其缺陷,并详细讨论了当前802.11无线局域网安全措施与技术.最后提出一种企业级应用方案.     

程序的调试技巧

该文简要介绍编程中常见的错误类型,通过黑箱测试法、白箱测试法、等价分类法、边界分析法和错误推测法对程序错误进行分析判断和定位。     

AgOx型超分辨近场结构的非线性光学特性研究

采用共焦Z扫描系统，以λ=532nm．脉冲宽度0．7ns．重复频率15．79kHz的脉冲半导体激光器作为入射光源，研究了AgOx超分辨近场结构(SuperRENS)薄膜样品的非线性光学性质．实验获得了其三阶非线性折射率系数随入射光功率的变化曲线．并与Au，Ag薄膜作了比较．讨论了光致非线性变化过程。结果表明，在聚焦激光作用下．AgOx超分辨近场结构薄膜样品存在一相变点．即解析出纳米Ag颗粒，满足了产生局域表面等离子体的激发和增强效应的条件。     

Array-index: a plug&search K nearest neighbors method for high-dimensional data

Previous algorithms of data partitioning methods (DPMs) to find the exact K-nearest neighbors (KNN) at high dimensions are outperformed by a linear scan method [J.M. Kleinberg, Two algorithms for nearest neighbor search in high dimensions, 29th ACM Symposium on Theory of computing, 1997; R. Weber, H.-J. Schek, S. Blott. A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. in: Proc. of the 24th VLDB, USA, 1998]. In this paper, we present a “plug&search” method to greatly speed up the exact KNN search of existing DPMs. The idea is to linearize the data partitions produced by a DPM, rather than the points themselves, into a one-dimensional array-index, that is simple, compact and fast. Unlike most DPMs that support KNN search, which require storage space linear, or exponential [J.M. Kleinberg, Two algorithms for nearest neighbor search in high dimensions, 29th ACM Symposium on Theory of computing, 1997; M. Hagedoom, Nearest neighbors can be found efficiently if the dimension is small relative to the input size, ICDT 2003], in dimensions, the array-index requires a storage space that is linear in the number of mapped partitions.