改进的分层A*算法在停车场路径寻优中的应用

在大型停车场车位路径寻优中,传统的评价指标是把距离最短作为最优指标,并没有考虑实际路况,为此引入了切实可行的时间较优评价指标,既能简化引导系统硬件设计,又能节省软件开销;首先,建立了停车场网络图R (P,C,D,V)数学模型,并把网络中的所有节点分成两层,分别构建了不同的估价函数,采用改进的A*算法,提高了以时间较优为评价指标的路径搜索效率和搜索精度;最后,程序运行结果表明,针对不同的路段属性参数,算法总能较快的找到时间较优路径.     

一种复杂环境下移动机器人避障新方法

为解决基于传统人工势场法的机器人避障算法在陷阱区域或在障碍物前会产生震荡而导致机器人不能到达目标点的问题,提出一种带记忆功能的沿边法;通过记录和分析障碍物边缘人工势场法的局部最小点来判断目标点是否被障碍物包围,从而避免机器人来回震荡以及围着目标点旋转的现象;首先进行沿边行为激活和退出条件研究,然后进行局部最小点记录条件分析,最后给出了目标点被障碍物包围的判断准则;仿真实验,结果表明该方法解决了复杂环境下机器人的避障问题;该方法用于复杂环境下的机器人避障是可行的、有效的.     

红外成像系统噪声等效温差参数测试算法及应用研究

噪声等效温差(NETD)是表征红外成像系统灵敏度的关键参数,也是评估红外成像系统性能的重要参数之一,应用广泛。通过对红外成像系统3D噪声、信号传递函数(SiTF)、NETD等参数测试方法、算法和流程研究,给出一种基于视频文件的3D噪声离线对比测试方法和一种SiTF线性区自动判断计算斜率算法,在此基础上针对某型技术保障装备国产化光电检测平台开发了配套应用软件功能模块;实现了通过计算单位均方根噪声所对应的SiTF斜率值,分析得出系统NETD参数值的功能;以某型热像仪为被测对象,开展了测试结果重复性和一致性试验,并与I-SITE红外整机测试系统进行了对比测试;实验结果表明开发的NETD参数测试功能模块测试精度和重复性满足设计要求,具有较高实用价值,已进行了工程应用。     

基于参数自适应模糊PI的三级倒立摆控制

三级倒立摆作为高阶次、多变量、非线性、强耦合的不稳定系统,不易对其进行有效控制.在基本模糊控制器基础上,设计了一种参数自适应模糊PI控制器.即通过LQR(Linear Quadratic Regulator)最优控制理论方法,确定出融合函数,降低了模糊控制器的输入维数,减少了控制器规则数.经过参数修正模糊控制器,实现参数自适应调整,提高了系统控制性能.通过SIMULINK仿真及对比,结果显示,系统能在较短时间内达到稳定,控制效果、稳定性及鲁棒性均较好,能满足系统要求.     

交互式遗传程序设计在作曲中的应用

针对目前的算法作曲系统普遍存在的局限性,提出一种交互式遗传程序设计(Interactive Genetic Programming,IGP)的作曲方法.介绍了用交互式遗传程序设计进行作曲的原理、步骤.提出了一种交互式遗传程序乐曲生成系统,用人做为适应度函数,用遗传程序设计的方法来产生乐曲片段.把乐曲片段交给人进行评价后,人对乐曲是否参与下一代进化进行取舍,直至产生理想的乐曲.实验结果显示:得到的乐曲片段较之前各种乐曲生成系统得到的乐曲更连贯,能够符合人的欣赏习惯.     

基于MMTD算法的粒子群的解Ⅱ

粒子群算法是一种寻找最优解的算法,该算法在寻找的过程中需要粒子所得的目前解具有判断力和记忆力.然而正是由于该算法中的粒子对当前的解具有判断力,才能够使得粒子群中的粒子能够较快地找到最优解.粒子群中的粒子在求解过程中所得的结果可分为三种:优,中,差,这三种解的属性符合中介思想.然而MMTD的算法正是中介思想的一种应用,因此论文将MMTD算法在粒子群上进行应用,该算法能够对粒子群解的属性上做出判断.     

C语言函数教学方法探讨

函数是程序的基本组成单位,是C语言程序设计课程的核心部分。结合多年的教学实践,探讨了函数教学的一些行之有效的教学方法,供同行参考。     

Key management in tree shaped hierarchies

ABSTRACT

We refer to an access control system based on subjects and objects. Subjects are active entities, e.g. processes, while objects are passive entities, e.g. messages exchanged between the nodes of a distributed computing environment. The system is partitioned into security classes organized into a tree shaped hierarchy. A subject assigned to a given class can access the objects in this class and in all the classes that descend from this class in the class hierarchy. To this aim, a key is associated with each class. A mechanism of the protection system, called key derivation, allows a subject that holds the key of a given class to transform this key into the keys of the descendant classes. This mechanism is based on a single, publicly known one-way function. If the class hierarchy is modified, by adding a new class or deleting an existing class, the necessary form of key redistribution is partial, and is limited to the classes in the subtree of the root that is involved in the change.     

Multi-target tracking on confidence maps: An application to people tracking

We propose a generic online multi-target track-before-detect (MT-TBD) that is applicable on confidence maps used as observations. The proposed tracker is based on particle filtering and automatically initializes tracks. The main novelty is the inclusion of the target ID in the particle state, enabling the algorithm to deal with unknown and large number of targets. To overcome the problem of mixing IDs of targets close to each other, we propose a probabilistic model of target birth and death based on a Markov Random Field (MRF) applied to the particle IDs. Each particle ID is managed using the information carried by neighboring particles. The assignment of the IDs to the targets is performed using Mean-Shift clustering and supported by a Gaussian Mixture Model. We also show that the computational complexity of MT-TBD is proportional only to the number of particles. To compare our method with recent state-of-the-art works, we include a postprocessing stage suited for multi-person tracking. We validate the method on real-world and crowded scenarios, and demonstrate its robustness in scenes presenting different perspective views and targets very close to each other.