超大规模集成电路电源完整性设计中的滤波电容选择

集成电路技术的迅速发展,对电源完整性设计提出了更高的要求,设计者通常通过放置各种电容来降低电源噪声以及应对负载瞬态大电流的需求。讨论了电容技术发展对电源完整性设计带来的影响,同时通过对几种典型电容特性的分析,给出了在电源完整性设计中合理选择使用各种滤波电容的解决方案。     

STM32F107的停车引导系统设计

本文设计的停车诱导系统以STM32F107微控制器为核心处理器,由RFID读卡器组成检测电路,用来检测停车场的车辆通过情况;有源RFID的无线模块发送信号,由检测模块将检测信号上传至上位机,由上位机控制停车场地面的指示灯(用来指示是否有车辆通过)的开启与关闭.采用Modbus通信协议进行控制和监控,实现了与外界环境相结合的人为可控智能闭环系统.     

RadarSat-2全极化数据土地覆盖分类精度评价

Radar Sat-2全极化数据能否应用于土地覆盖分类需要大量的研究和论证。本文以NLCD为参考数据,利用SVM分类器对1景旧金山地区Radar Sat-2全极化数据进行土地覆盖分类实验,并从分类类别面积一致性、空间相似性两个方面对分类结果进行分类精度评价。实验获得Radar Sat-2数据分类结果总体分类精度76.91%和kappa系数0.65,表明Radar Sat-2全极化数据用于土地覆盖分类分类精度较高,可以达到很好的分类质量。     

Exponential stability of stochastic singular delay systems with general Markovian switchings

In recent years, Markovian jump systems have received much attention. However, there are very few results on the stability of stochastic singular systems with Markovian switching. In this paper, the discussed system is the stochastic singular delay system with general transition rate matrix in terms of uncertain and partially unknown transition rate matrix. The aim is to answer the question whether there are conditions guaranteeing the underlying system having a unique solution and being exponentially admissible simultaneously. The proposed results show that all the features of the underlying system such as time delay, diffusion, and general Markovian switchings play important roles in the system analysis of exponential admissibility. A numerical example is used to demonstrate the effectiveness of the proposed methods. Copyright © 2014 John Wiley & Sons, Ltd.     

Approximate dynamic programming via iterated Bellman inequalities

In this paper, we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based on solving linear or semidefinite programs, and produces both a bound on the optimal objective, as well as a suboptimal policy that appears to works very well. These results extend and improve bounds obtained in a previous paper using a single Bellman inequality condition. We describe the methods in a general setting and show how they can be applied in specific cases including the finite state case, constrained linear quadratic control, switched affine control, and multi‐period portfolio investment. Copyright © 2014 John Wiley & Sons, Ltd.     

Informative conditions for a data set in a MIMO closed‐loop system with a switching controller

In system identification, a data set needs to be informativeto ensure that the identification criterion has a unique global minimum asymptotically, and the parameter estimation is consistent. To guarantee a data set in a MIMO closed‐loop system with a switching controller to be informative, we develop a group of flexible conditions for the controller's switching rule and feedback laws, which provide a trade‐off between these two aspects through adjustable parameters. Compared with the results in the existing literature, our result includes all kinds of switching rules and therefore is not limited by the constraints on the switching rule.Copyright © 2014 John Wiley & Sons, Ltd.     

Less conservative stability criteria for linear systems with interval time‐varying delays

The problem of the stability of a linear system with an interval time‐varying delay is investigated. A new Lyapunov–Krasovskii functional that fully uses information about the lower bound of the time‐varying delay is constructed to derive new stability criteria. It is proved that the proposed Lyapunov–Krasovskii functional can lead to less conservative results than some existing ones. Based on the proposed Lyapunov–Krasovskii functional, two stability conditions are developed using two different methods to estimate Lyapunov–Krasovskii functional's derivative. Two numerical examples are given to illustrate that the two stability conditions are complementary and yield a larger maximum upper bound of the time‐varying delay than some existing results. Copyright © 2013 John Wiley & Sons, Ltd.     

Nonconvex plus quadratic penalized low-rank and sparse decomposition for noisy image alignment针对含噪图像对准问题的非凸加二次罚项约束的低秩和稀疏分解方法

This paper proposes a general method for dealing with the problem of recovering the low-rank structure, in which the data can be deformed by some unknown transformations and corrupted by sparse or nonsparse noises. Nonconvex penalization method is used to remedy the drawbacks of existing convex penalization method and a quadratic penalty is further used to better tackle the nonsparse noises in the data. We exploits the local linear approximation (LLA) method for turning the resulting nonconvex penalization problem into a series of weighted convex penalization problems and these subproblems are efficiently solved via the augmented Lagrange multiplier (ALM). Besides comparing with the method of robust alignment by sparse and low-rank decomposition for linearly correlated images (RASL), we also propose a nonconvex penalized lowrank and sparse decomposition (NLSD) model as comparison. Numerical experiments are conducted on both controlled and uncontrolled data to demonstrate the outperformance of the proposed method over RASL and NLSD.