曲面轮廓矩不变量及其应用

传统三维矩不变量的计算方法基于区域特征,计算量较大.将基于区域的三维矩不变量计算转化到三维物体曲面轮廓上,构造了一种的新的曲面轮廓矩不变量.此不变量减小了计算复杂度,不仅具有平移、尺度和旋转不变性,而且独立于三维物体本身的颜色和灰度级.仿真实验表明,基于曲面轮廓矩不变量的识别算法对于三维目标具有良好的识别率,减小了计算复杂度.另外,对这种矩不变量在基于颜色、灰度等识别场合的应用做了推广.     

基于离散动态贝叶斯网络的辐射源目标识别研究

提出基于离散动态贝叶斯网络模型,对若干可观测的目标特征参数进行综合推理.推导了离散动态贝叶斯网络的推理算法.建立了目标识别的离散动态贝叶斯网络模型.应用图形模式,使得计算量大大简化,降低了实用的复杂性.仿真结果表明,该方法能够将各种目标特征进行综合,使得各种特征及不同时刻的同一特征互相修正补充,克服了依靠单一特征进行目标识别的局限.     

多联机室内机制冷剂管网流量分配仿真模型

针对多联机室内机制冷剂管网中制冷剂流量分配不均,将流体网络理论应用于包含蒸发器、管段、电子膨胀阀、三通等单相、两相制冷剂的复杂管网系统,按照管网拓补结构连接各个部件模型,得到了5台室内机及连接管构成的管网的稳态仿真模型;针对流阻的非线性特点设计了以每两个相邻环路压降之差小于50Pa作为控制条件的迭代算法,根据流阻分配各个环路流量直至管网达到压强平衡.该模型可以研究、评价制冷剂流量分配不均程度,为解决多联机流量分配不均提供理论依据.     

不确定的多商品流多准则供应链网络模型

基于供应链网络中同层成员的相互竞争以及不同层成员间的相互合作关系,构建了不确定条件下由制造商、分销商和零售商组成具有多准则决策的多商品流供应链网络模型.研究了制造商和分销商的多准则决策,零售商在市场需求不确定条件下进行决策,同时考虑了制造商和零售商之间的直销关系.利用变分不等式的形式给出了供应链网络中各层以及整体的均衡条件和相应的经济解释.最后,通过算例说明了模型的合理性.     

Knight不确定环境下供应商的乐观度对定价决策的影响

针对供应商的可变成本和产品市场价的双重Knight不确定性,本文运用α-maxmin多先验期望效用和纳什讨价还价模型研究了供应商的定价问题,涉及固定价格、成本加成和参考市场价三种合同,剖析了供应商的乐观度和含糊度对这些定价决策的影响。结论表明,固定价格随着供应商对成本的乐观度的提高而降低,随着市场价的乐观度的提高而提高.成本(市场价)的乐观度决定着成本(市场价)的含糊度与定价结果的关系.参考市场价合同下,供应商的定价权威不影响目标价格与成本的乐观度的关系,但影响目标价格与市场价的乐观度之间的关系。上述研究为分析不确定环境下供应商的定价行为提供理论支持。     

不确定云环境下基于滚动窗口的节能调度

目前,绿色云计算已经成为工业界和学术界的研究热点. 然而,以往的绿色节能调度研究忽略了虚拟机性能的不确定因素,使得调度效果与实际情况相差甚远. 本文提出一种基于滚动窗口的节能调度算法（ERRHU）,用于动态调度不确定云环境中的实时任务,同时根据系统的负载动态伸缩系统的计算资源以减少系统的能量消耗. 本文通过大量的模拟实验比较ERRHU与其他算法的性能.     

Underdetermined DOA estimation and blind separation of non-disjoint sources in time-frequency domain based on sparse representation method

This paper deals with the blind separation of nonstation-ary sources and direction-of-arrival （DOA） estimation in the under-determined case, when there are more sources than sensors. We assume the sources to be time-frequency （TF） disjoint to a certain extent. In particular, the number of sources presented at any TF neighborhood is strictly less than that of sensors. We can identify the real number of active sources and achieve separation in any TF neighborhood by the sparse representation method. Compared with the subspace-based algorithm under the same sparseness assumption, which suffers from the extra noise effect since it can-not estimate the true number of active sources, the proposed algorithm can estimate the number of active sources and their cor-responding TF values in any TF neighborhood simultaneously. An-other contribution of this paper is a new estimation procedure for the DOA of sources in the underdetermined case, which combines the TF sparseness of sources and the clustering technique. Sim-ulation results demonstrate the validity and high performance of the proposed algorithm in both blind source separation （BSS） and DOA estimation.     

Group consensus for multiple networked Euler-Lagrange systems with parametric uncertainties

In this paper,a group consensus problem is investigated for multiple networked agents with parametric uncertainties where all the agents are governed by the Euler-Lagrange system with uncertain parameters.In the group consensus problem,the agents asymptotically reach several different states rather than one consistent state.A novel group consensus protocol and a time-varying estimator of the uncertain parameters are proposed for each agent in order to solve the couple-group consensus problem.It is shown that the group consensus is reachable even when the system contains the uncertain parameters.Furthermore,the multi-group consensus is discussed as an extension of the couple-group consensus,and then the group consensus with switching topology is considered.Simulation results are finally provided to validate the effectiveness of the theoretical analysis.     

Consensus design for continuous-time multi-agent systems with communication delay

This paper investigates a consensus design problem for continuous-time first-order multiagent systems with uniform constant communication delay.Provided that the agent dynamic is unstable and the diagraph is undirected,sufficient conditions are derived to guarantee consensus.The key technique is the adoption of historical input information in the protocol.Especially,when agent＇s own historical input information is used in the protocol design,the consensus condition is constructed in terms of agent dynamic,communication delay,and the eigenratio of the network topology.Simulation result is presented to validate the effectiveness of the theoretical result.     

Further results on limitations of sampled-data feedback

To control continuous-time uncertain dynamical systems with sampled data-feedback is prevalent today,but the sampling rate is usually not allowed to be arbitrarily fast due to various physical and/or computational constrains.In this paper,the authors examine the limitations of sampled-data feedback control for a class of uncertain systems in continuous-time,with sampling rate not necessary fast enough and with the unknown system structure confined to a set of functions with both linear and nonlinear growth.The limitations of the sampled-data feedback control for the uncertain systems are established quantitatively,which extends the existing related results in the literature.