Robust Stabilization of Discrete time Constrained Singular Piecewise affine Systems with Norm bounded Uncertainties

In this paper,the problem of designing robust H-infinity output feedback controller and l2-gain controller are investigated for a class of discrete-time singular piecewise-affine systems with input saturation and state constraints. Based on a singular piecewise Lyapunov function combined with S-procedure and some matrix inequality convexifying techniques,the H-infinity stabilization condition is established and the l2-gain controller is investigated,and meanwhile,the input saturation disturbance tolerance condition is proposed. Under energy bounded disturbance,the domain of attraction is well estimated and the l2-gain controller is designed in some restricted region. It is shown that the controller gains can be obtained by solving a family of LMIs parameterized by one or two scalar variables. Meanwhile,by using the corresponding optimization methods,the domain of attraction and the disturbance tolerance level is maximized,and the H-infinity performance γ is minimized.Finally,numerical examples are given to illustrate the effectiveness of the proposed design methods.     

基于Walsh信号空间分解的CPM序列检测算法*

连续相位调制本身所具有的高效频谱和功率利用率使得这种调制方式非常适用于无线通信环境中,但其解调的复杂度也随着记忆长度和进制数的增加呈指数增长。该文给出了基于Walsh信号空间分解的序列检测算法,将接收机前端大量的匹配滤波器替换为两个低通滤波器加子区间采样器,这样有效地降低了CPM解调器前端复杂度,并通过对最小投影距离损失的分析,得出了一个关于接收机使用Walsh信号空间维数所遵循的最低限准则,并通过仿真验证了这个准则是有效的。     

Point Light Source Estimation from Two Images and Its Limits

In this paper, the performance of parameter estimation of a single static distant point light source from two video images is analyzed in terms of estimation theory. The illumination parameters are the intensity and direction of the light source.In the first part of this paper, estimators from the literature are reviewed. Most recent estimators evaluate as input data two video images as well as the 3D shape and the 3D motion of the visible moving objects.In the second part of the paper, the performance of these recent methods is analyzed. The input data to estimation as well as the inherent input data errors are described by a stochastic observation model. Based on this model, the performance is analyzed regarding the Cramér-Rao theoretical lower bound of estimation error variances. The bound is derived for a variety of cases of scene illumination, object motion and errors in input data. For simplification purpose, the bound is valid only for object motions with the rotation axis lying in the image plane. The analysis shows in which cases which estimation accuracy can be expected with current methods.Finally, a comparison of the bound with one of the recent estimators shows that recent estimators are suboptimal in case of errors in the 3D shape of the objects. In future work, the stochastic observation model presented in this paper can be used to improve illumination estimation.     

A computationally efficient approach for hidden-Markov model-augmented fingerprint-based positioning

This paper presents a computationally efficient approach for mobile subscriber position estimation in wireless networks. A method of data scaling assisted by timing adjust is introduced in fingerprint-based location estimation under a framework which allows for minimising computational cost. The proposed method maintains a comparable level of accuracy to the traditional case where no data scaling is used and is evaluated in a simulated environment under varying channel conditions. The proposed scheme is studied when it is augmented by a hidden-Markov model to match the internal parameters to the channel conditions that present, thus minimising computational cost while maximising accuracy. Furthermore, the timing adjust quantity, available in modern wireless signalling messages, is shown to be able to further reduce computational cost and increase accuracy when available. The results may be seen as a significant step towards integrating advanced position-based modelling with power-sensitive mobile devices.     

一种基于极大似然准则的自适应卡尔曼滤波算法

在系统不能确切建模或模型本身会产生改变的应用场合，传统卡尔曼滤波算法的性能受到直接影响，甚至无法正常应用。基于标准卡尔曼滤波假设，利用极大似然估计准则推导了一种新的自适应卡尔曼滤波算法，这种滤波算法的主要思路是利用新息序列对系统和量测噪声方差阵Q和R实时估计和调整，以实时反映系统模型的变化。在相关理论分析的基础上，针对低成本惯性／GPS组合导航系统对这种自适应卡尔曼滤波方法的性能进行了仿真分析，与传统卡尔曼滤波算法进行了比较，探讨了这种算法的实用性。     

2400b／s短波串行数传MODEM

此文介绍了一种2400b/s短波串行数传MODEM。该系统采用了预判决反馈和简化维特比算法的准最大似然序列检测技术、交错里德——索罗蒙码的前向纠错技术及高速数字信号处理技术等。线路试验结果表明,该MODEM系统在抗加性噪声干扰和多径衰落方面都达到了良好的性能。     

一种新的准正交空时分组码的设计

ABBA码是一种可用于3个以上发射天线系统的准正交空时分组码,该方案虽然可以实现全速率传输,但是其译码复杂度高。针对上述缺点提出了一种基于星座旋转的能够实现满分集增益、全速率传输的准正交空时分组码,给出了接收端最大似然译码的独立译码方案,简化了译码过程,降低了译码复杂度,仿真结果表明其误码性能与ABBA码相比得到了较大的改善。     

两种定时同步算法的讨论与分析

介绍基于最大似然准则的定时同步算法,通过仿真发现该算法应用于AWGN信道效果很好,但是应用于平坦衰落信道效果相对较差。为了解决信号在平坦衰落信道传输过程中遇到的一系列问题,对基于循环平稳特性的定时同步算法进行了研究和改进。仿真结果表明该算法可以很好地适应于衰落信道。     

一种基于PHM考虑老化和设备状态的油浸式变压器故障率模型

比例故障率模型(Proportional hazard model, PHM)中的故障率函数包含基准故障率函数和连接函数,前者表征设备的一般老化,后者描述设备状态的影响,对不同影响因素(协变量)进行量化。基于 PHM提出了一种综合考虑老化和设备状态的油浸变压器故障率模型,基准故障率函数采用常用的温升老化模型,连接函数中的协变量选择了能够全面客观反映设备状况的油中溶解气体信息。推导了故障前时间的概率密度分布并给出了使用极大似然估计拟合参数的方法。算例证明了拟合方法的正确性,结果分析表明提出的模型具有正确合理表征故障率的能力,并且能有效表征变压器维护操作对故障率的影响。     

极大似然反卷积软件包

本文介绍了用于石油和天然气勘探的一种新型的、高分辩率的极大似然反卷积算法的软件包,详细阐述了该软件包的基本原理、结构和特点。