基于内部EEPROM的自动电子定时开关的设计

给出了一种基于STC89C51RC单片机的电子定时开关的设计方案,利用时钟芯片DS1302进行走时,由单片机STC89C51RC的内部EEPROM记忆断开和闭合的时间数据,当定时开关断电重启时,仍能够按已设置的时间间隔运行,避免了重新设置.     

基于GSM的远程车载防盗报警系统设计

提出了一种基于SIM300的车载无线防盗报警装置。该方案主要由单片机和SIM300模块两部分组成,借助成熟的GSM移动网络,以直观的中文短消息或电话形式进行无线控制,将控制与监测实现了智能化、便捷化及远程化。     

一种JPEG图像的DCT域隐写分析方法

提出了一种基于JPEG图像DCT系数差分矩阵统计特征的隐写分析方法。该算法保留了以往算法选用的DCT系数水平和竖直方向的差分矩阵相关特征,通过增加其主副对角线方向上差分矩阵来提取和计算特征向量,进而利用SVM分类器进行分类。实验结果表明,该方法能够有效地对JPEG图像进行检测,并且具有较高的检测正确率。     

基于WebKit的嵌入式浏览器关键技术研究与实现

随着嵌入式设备的大量普及,具有自主知识产权嵌入式浏览器的研究也逐步深入.通过对WebKit的基本框架的分析,研究了其关键技术,并针对特定的硬件平台进行了移植和裁剪,实验表明该研究为自主知识产权浏览器的开发提供了重要的参考价值.     

使用Visual C++实现多媒体电子出版物中的矢量电子地图

该文介绍在基于光盘的多媒体电子出版物中实现矢量电子地图的关键技术。使用VisualC＋＋和面向对象的方法实现了一个矢量电子地图引擎。     

基于图像特征配准的数字血管减影算法

数字减影血管成象(DSA)是一种在医学诊断以及介入治疗中起重要作用的技术。在临床应用中,由于能源能量的波动、设备噪声、病人移动、器官蠕动等,通常的数字减影结果常常出现伪影。伪影消除问题成为数字减影技术中的难点,也是引起关注的热点。文章提出了消除伪影的一套新的算法———基于图像局部特征消除伪影。包括建立排除模板、控制点判定准则与方法、位移向量优化、配准方法等。该方法已用VC编制成软件,并且装备数字化X-射线装置,在计算机试验及临床实验中都取得了满意的效果。     

防火墙及其安全策略

本文论述了Firewall技术的基本特征及安全方面的策略。     

Adaptive guidance law design based on characteristic model for reentry vehicles

In this paper an adaptive guidance law based on the characteristic model is designed to track a reference drag acceleration for reentry vehicles like the Shuttle. The characteristic modeling method of linear constant systems is extended for single-input and single-output （SlSO） linear time-varying systems so that the characteristic model can be established for reentry vehicles. A new nonlinear differential golden-section adaptive control law is presented. When the coefficients belong to a bounded closed convex set and their rate of change meets some constraints, the uniformly asymptotic stability of the nonlinear differential golden-section adaptive control system is proved. The tracking control law, the nonlinear differential golden-section control law, and the revised logical integral control law are integrated to design an adaptive guidance law based on the characteristic model. This guidance law overcomes the disadvantage of the feedback linearization method which needs the precise model. Simulation results show that the proposed method has better performance of tracking the reference drag acceleration than the feedback linearizaUon one.     

Robust neural network tracking controller using simultaneous perturbation stochastic approximation

This paper considers the design of robust neural network tracking controllers for nonlinear systems. The neural network is used in the closed-loop system to estimate the nonlinear system function. We introduce the conic sector theory to establish a robust neural control system, with guaranteed boundedness for both the input/output (I/O) signals and the weights of the neural network. The neural network is trained by the simultaneous perturbation stochastic approximation (SPSA) method instead of the standard backpropagation (BP) algorithm. The proposed neural control system guarantees closed-loop stability of the estimation system, and a good tracking performance. The performance improvement of the proposed system over existing systems can be quantified in terms of preventing weight shifts, fast convergence, and robustness against system disturbance.     

Comments on “A new robust control for a class of uncertaindiscrete-time systems”

A completed proof for a theorem on the robust controller design proposed in Wang and Ghosh (ibid. vol.43 (1997)) is presented in this paper