一种改进的视网膜图像中微小动脉瘤的检测算法

基于糖尿病性视网膜病变中最早出现的微小动脉瘤病症进行了研究,提出一种有效的微小动脉瘤检测算法。首先在传统模板匹配算法的基础上提出了一种动态多参数模板匹配算法,并且使用相对误差和与相关系数来共同制约匹配度,从而实现了更为精确的匹配提取;其次提出了基于分布特性的计分策略和自适应加权的汇总策略,避免了单纯采用各个特征量作为独立约束指标进行筛选时忽视各个特征量的约束力大小的弊端。实验结果表明,该检测算法能够有效地提高微小动脉瘤的检测真阳性率。     

参数计算中使用的若干技术

参数计算和复杂性是上世纪末本世纪初兴起的一门技术。该技术因具有坚实的理论基础和良好的运行效果,故仅经过短短十几年的发展,已经取得了大量的成就。从趋势上看来,参数计算已经成为理论计算机科学中越来越热门的一个分支。先简要介绍参数计算和复杂性的重要理论基础和主要思想;之后重点介绍参数计算中使用的主要技术,分析每一种技术的功能作用、基本设计原则和优缺点,并结合简单案例加以说明。     

流变参数对顺序共注成型芯层熔体最大填充量的影响

基于Hele-Shaw模型，采用有限元数值模拟技术，系统研究了壳层熔体流变指数和零切黏度对顺序共注成型芯层熔体最大填充量的影响规律，并基于流变学理论揭示了其影响机理，最终提出了顺序共注成型芯层熔体最大填充量与壳层熔体流变指数和零切黏度经验关系方程。     

一类混合延迟混沌神经网络的同步

时滞混沌神经网络系统是解空间为无穷维系统,可生成多个正向Lyapunov指数,产生具有高度随机性和不可预测性的混沌甚至超混沌序列,这种特性使得时滞混沌神经网络系统特别适用于保密通信中,混沌同步是保密通信中的关键技术。基于Lyapunov稳定性理论和线性矩阵不等式(LMI)方法,研究了一类具有时变延迟和分布式延迟的混沌神经网络系统的同步问题,考虑系统的内部参数不确定性和外部干扰及混合时滞等因素,将系统时滞项加入所设计的控制器中,给出了保证误差系统的全局均方渐近稳定的充分条件和控制律,实现驱动系统和响应系统的同步。与其它方法相比,所设计的含有时滞项的控制器提高了系统误差精度及反应速率。最后,通过仿真实例,验证了所提方法的有效性。     

巧用网游加速器为浏览器提速

使用过搜狗浏览器的用户都知道,它有一个网页加速的功能模块,在访问网速比较慢的时候,可以利用它加快网页访问速度。可是并不是所有的浏览器都有这项功能,其实我们可以利用一些网游加速器,借用它们的服务器为我们的浏览器进行加速。     

GCS雾化降温系统用于窑头烟气处理

我厂2500t/d熟料新型干法熟料生产线,于2003年12月开始试生产,其熟料冷却采用的是天津中天仕名公司开发的TC-1164往复推动冲气梁式篦冷机,窑头烟气量31.5万m3/h,经过篦冷机后温度约在220～250°的范围内,尾部处理采用电收尘器,按照设计中的工艺参数,生产过程中将可能出现烟气温度不稳的情况,若篦冷机突然发生红料,塌料现象,可能出现400℃的高温,为此电收尘器受到高温烟气造成管道和极板烧坏。为解决这一问题,我们采用安全降温措施,通过两种水雾降温,烟气在进入电收尘器之前调温调质,将烟气的比电阻调到最低,提高电收尘器的捕捉效率。通过方…     

Analysis and design of secure cyber-physical systems

Cyber-physical systems （CPSs） are new emerging systems that seamlessly integrate physical systems, communication systems and computation systems. Their wide use has been witnessed in the past decades in many crossdiscipline fields such as smart energy systems, industrial process control, aerospace and automobile engineering, health-care and assisted living, to just name a few. For many of these systems, secure operations are of key con- cerns. In particular, for some safety-critical applications, security is of paramount importance. Diverse motivations and strong incentives exist everywhere and at any time for launching malicious attacks on the CPSs, for example, economic reasons （e.g., by reducing or even not paying electricity charge） and terrorism the purpose of which is apparent.     

Robust state estimation for uncertain linear systems with deterministic input signals

In this paper, we investigate state estimations of a dynamical system in which not only process and measurement noise, but also parameter uncertainties and deterministic input signals are involved. The sensitivity penalization based robust state estimation is extended to uncertain linear systems with deterministic input signals and parametric uncertainties which may nonlinearly affect a state-space plant model. The form of the derived robust estimator is similar to that of the well-known Kalman filter with a comparable computational complexity. Under a few weak assumptions, it is proved that though the derived state estimator is biased, the bound of estimation errors is finite and the covariance matrix of estimation errors is bounded. Numerical simulations show that the obtained robust filter has relatively nice estimation performances.     

Introducing robustness in model predictive control with multiple modelsand switching

Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate an upper bound of the optimal value of this parameter are available. These procedures are computationally intensive and model-based. Besides, a single choice of this horizon is perhaps not the best option at all time instants. This is especially true when the control objective is to track desired trajectories. In this paper, we resolve the issue by a time-varying horizon achieved by switching between multiple model-predictive controllers. The stability of the overall system is discussed. In addition, an introduction of multiple models to handle modelling uncertainties makes the overall system robust. The improvement in performance is demonstrated through several examples.     

基于近似弧长参数化的机器人轨迹规划

主要研究了采用近似弧长参数化的插值方法进行关节式工业机器人的轨迹规划.运用近似弧长参数化的插值方法将机器人末端轨迹参数曲线离散为等弧长的插值点序列,通过机器人逆向运动学求解各关节的位移点序列,采用极限的方法进行各关节速度和加速度规划.这种轨迹规划方法可以避免关节空间的插值计算和雅克比矩阵的计算.在 matlab7.8平台上,对近似弧长参数化的插值方法、轨迹规划及可行性验证进行了实例仿真,仿真结果表明该轨迹规划方法是可行的.