Performance and EXIT analysis of parallel concatenated space time trellis codes

Space time trellis coding (STTC) techniques have been proposed to achieve both diversity and coding gains in multiple input multiple output (MIMO) fading channels. But with more transmit antennas STTCs suffer from the design difficulty and complexity increasing. This paper proposes a scheme, named parallel concatenated space time trellis codes (PC-STTC), to achieve the tradeoff between the performances and complexity of STTCs for a large number of transmit antennas. Simulation results and complexity comparison are provided to demonstrate the performance and superiority of the proposed scheme over conventional schemes in fast fading channels in low signal-to-noise ratio (SNR) regions. And an EXIT (extrinsic information transform) chart is given to analyze the iterative convergence of the proposed scheme. It shows that PC-STTC has better iterative convergence in low SNR regions.     

An Exact Logarithmic-exponential Multiplier Penalty Function

In this paper, we give a solving approach based on a logarithmic-exponential multiplier penalty function for the constrained minimization problem. It is proved exact in the sense that the global optimizers of a nonlinear problem are precisely the global optimizers of the logarithmic-exponential multiplier penalty problem.     

基于多普勒频移的双基地声纳目标速度测量

针对单基地声纳仅可获得目标的径向速度以及双基地声纳有大量冗余信息的问题,提出利用单/双基地复合工作的声纳系统求解目标二维速度矢量（速度大小、航向）的方法。为了获得目标的二维速度矢量,在双基地声纳系统中,分析了双基地声纳多普勒频移的特性,并与单基地作了比较;结合单、双基地所获得的多普勒频移特性信息,给出了目标二维速度矢量的两种计算方法;并对目标速度测量误差进行了分析。结果表明,采用单/双基地复合工作的声纳系统,可以完成目标二维速度矢量的测量,而测量误差则与系统的频移分辨力及目标与收、发基地间的相对位置有关。     

基于HTCP-net的multi-agent调度系统建模与仿真

从企业收集、监测互联网信息的实际需求出发,提出了基于multi-agent的分布式环境扫描系统的结构模型;同时,为满足系统重复采集更新信息的特殊需要,借鉴经典的Min-min启发式调度算法,设计了循环任务最早完成时间调度算法。依据赋时层次有色Petri网(HTCP-net)的理论,应用建模、仿真工具CPN tools建立了调度系统模型。对模型进行仿真,得到任务平均等待时间和各agent等待队列平均长度,与轮转调度和最短等待队列调度模型仿真结果的比较表明,所建立的调度模型既提高了企业用户满意度,又有效满足了系统周期性重复访问网站的任务需求。     

一类不确定时延网络控制系统的模糊控制

针对网络控制系统(NCS)同时存在网络诱导时延和数据包丢失的情况,讨论了如何设计控制器的问题。首先,给出了一种新的闭环网络控制系统的建模方法——模糊T-S方法,利用这种模糊模型去逼近非线性网络控制系统,使之局部线性化,并在此模型的基础上应用平行分布补偿原理设计了网络控制系统模糊控制器。进而,应用Lyapunov理论和LMI方法,研究了模糊NCS的稳定性问题,同时基于线性矩阵不等式给出依赖状态时滞和网络诱导时延的状态反馈模糊控制器的设计方法,并获得使模糊NCS稳定的充分条件。通过两个仿真实例验证了该控制方法的有效性。     

Robust H2 control for uncertain sampled-data systems

A new approach is proposed for robust H2 problem of uncertain sampled-data systems. Through introducing a free variable, a new Lyapunov asymptotical stability criterion with less conservativeness is established. Based on this criterion, some sufficient conditions on two classes of robust H2 problems for uncertain sampled-data control systems are presented through a set of coupled linear matrix inequalities, Finally, the less conservatism and potential of the developed results are illustrated via a numerical example.     

新农村建设之系统工程刍议

社会主义新农村建设是一项伟大的系统工程,其意义重大,影响深远.推进与实现这一伟大系统工程,就必须深刻理解其内容的丰富性,注重物质文明、政治文明、精神文明、生态文明建设有机结合与综合协调的发展,防止与避免单求建新房、换新貌的片面性;就必须确切把握其结构的层次性,处理好时空秩序、内容结构、主次矛盾等问题以及相互之间的关系,防止与避免不分头绪,急于求成的急躁性;、就必须充分认识其模式的多样性,多元化推进与发展各具特色的新农村,防止与避免搞一个模式、一种套路的强制性;就必须全面了解其建设的过程性,并明确长期性、艰巨性、动态性以及连续性和阶段性等发展过程中的特点,注意防止与避免搞政绩工程与形象工程的冒进性.     

信息——复杂生成的系统机缘

系统科学的当代发展必须在信息本质和机理上实现突破.信息是与质料、能量、时间、空间并立的存在要素之一,是事物固有的自在的结构、构造与形态及其表征.要描述刻画复杂、和谐与智能须建立质、能、息、时、空的统一理论.信息乃复杂之基因、和谐之引子、智能之成理.     

High efficient moving object extraction and classification in traffic video surveillance

Moving object extraction and classification are important problems in automated video surveillance systems. A background model based on region segmentation is proposed. An adaptive single Gaussian background model is used in the stable region with gradual changes, and a nonparametric model is used in the variable region with jumping changes. A generalized agglomerative scheme is used to merge the pixels in the variable region and fill in the small interspaces. A two-threshold sequential algorithmic scheme is used to group the background samples of the variable region into distinct Gaussian distributions to accelerate the kernel density computation speed of the nonparametric model. In the feature-based object classification phase, the surveillance scene is first partitioned according to the road boundaries of different traffic directions and then re-segmented according to their scene localities. The method improves the discriminability of the features in each partition. AdaBoost method is applied to evaluate the relative importance of the features in each partition respectively and distinguish whether an object is a vehicle, a single human, a human group, or a bike. Experimental results show that the proposed method achieves higher performance in comparison with the existing method.     

Portfolio Selection with Different Borrowing-Lending Rates: Utility Maximization Model based on Mean and VaR

This article investigates a portfolio selection problem with different borrowing–lending rates and with Value-at-Risk (VaR) as the measure of risk. The problem is formulated as a utility maximization model with a general utility function that is a function of only the mean and the VaR of portfolio return. Several properties of the efficient frontier of the mean-VaR model are first obtained and then used to give some existence conditions and characterizations of the optimal solution to the utility maximization model. Further, a solution method and a numerical algorithm for solving the optimal solution are proposed. Finally, a numerical example using the real data of Chinese stock market is given to show the validity and the practicability of these results.