一种新的基于压缩感知的WSN多目标定位方法

考虑无线传感器网络中定位信息的不完备性,将传感器网络监控区域划分成多个小网格,节点与目标随机分布于网格中,以目标位置信息为稀疏向量,提出了一种新的基于压缩感知的多目标定位方法。该方法将传感器节点感知到的目标数测量矩阵表示为压缩感知理论中测量矩阵、稀疏矩阵与稀疏向量的乘积形式,通过稀疏信号的重构算法恢复目标位置稀疏向量,实现多目标定位。考虑到感知矩阵不满足受限等距性条件,对此矩阵进行了正交化处理,使其满足重构算法的要求。通过仿真分析了节点感知半径、待定位目标数、传感器节点数对目标定位性能的影响。仿真结果表明,在定位信息不完备的情况下,上述方法能够满足无线传感器网络的目标定位要求,且该方法不依赖于硬件测距,其计算复杂度和定位精度与基于接受信号强度(RSS)的压缩感知定位算法相当。     

基于压缩感知的多目标定位中的测量矩阵设计

根据传感器网络中定位问题天然的稀疏性,研究了基于压缩感知理论的多目标定位方法。首先将目标位置信息表示成一个稀疏向量,将定位问题转化为向量估计问题。通过部署少量传感器测量接收信号的强度值,求解一个₁范数最优化问题便可精确地重构出位置向量。相对于当前压缩感知定位中常用的稀疏随机测量矩阵,提出了一种改进的测量矩阵设计方法,指示传感器节点进行有规律、均匀的部署。仿真结果表明,相较于传统随机测量矩阵,改进测量矩阵在定位精确度和稳定性上都体现了巨大优势。     

WSN中一种基于压缩感知的目标定位算法

针对目前的目标定位算法在定位误差等方面的不足,提出一种基于压缩感知的目标定位算法。将传感器网络划分为多个网格,相对于网格个数,目标个数是稀疏的,因此将目标定位问题转化为稀疏信号重构问题,基于目标的能量衰减特性设计测量矩阵,证明其满足RIP性质,并运用该算法来实现目标的精确定位。理论分析和仿真实验结果表明,该算法在目标定位误差及稀疏信号重构性能等方面优于传统的Binary等算法。     

基于压缩感知的多目标定位与功率估计

因传感器网络中定位问题具有的天然稀疏性,压缩感知理论被广泛应用于其中以减少数据采样量。然而,现有的基于压缩感知的定位技术往往需要目标的发射功率作为先验条件,这并不符合实际中目标完全未知的情况。基于此,提出了一种多目标定位和发射功率估计的方法,该方法将目标位置和功率信息建模成一个稀疏向量,从而将定位和功率估计问题转化为稀疏向量估计问题。该方法包括离线和在线两个阶段:离线阶段主要是部署一些射频发射器并测量接收信号强度值,从而构建感知矩阵;在线阶段中,通过部署少量传感器测量接收信号强度值,求解一个₁范数最优化问题便可精确地重构出稀疏向量。仿真结果验证了该多目标定位和功率估计方法的有效性和鲁棒性。     

基于数据融合的压缩感知多目标定位算法

文中提出一种基于数据融合的压缩感知多目标定位算法,该算法能够同时处理多种不同类型的定位数据。与传统算法相比,该算法以目标个数的稀疏性为基础,通过压缩感知技术来重构目标位置向量,从而大大减少了传感器的数目。算法分为数据预处理和数据融合定位两个阶段。在数据预处理阶段,将不同类型的数据转换到同一个数量级,使得各类型数据能被充分用于提高目标定位性能;在数据融合定位阶段,提出一种基于多测量向量的压缩感知重构算法来估计目标位置向量。仿真证明,相比于现有的压缩感知定位算法,所提算法具有更高的定位精度和更强的鲁棒性。     

基于网格扫描的实现目标点覆盖的确定性传感器节点部署方法

提出了一种确定性目标点覆盖算法,把目标点所在区域划分为若干正方形网格,从中选择最适合的网格作为下一个节点的放置位置;同时本文引入了概率感知模型,把节点能感知到目标点的最小感知概率值作为整体覆盖水平的评价指标,把节点能感知到目标点的个数及对它们的最小感知概率值作为网格的评价标准。该方法能使用最少的节点实现目标点覆盖并达到要求的总体覆盖水平,且能计算出较优的节点部署位置;对网格边长和感知概率下限的不同取值分别进行仿真实验。实验结果表明,网格边长越小,节点部署位置越精确;感知概率下限取值越大,总体覆盖性能越好,需要的节点越多。     

无线传感网络中目标定位的研究

在无线传感网络WSNs(Wireless Sensor Networks)中,现存的基于压缩感知的目标定位算法是假定目标均落在预定网格,当不满足此假设时,将极大地降低了目标定位算法的性能.为此,提出基于变分贝叶斯期望最大化的目标定位VBEM-TL (Variational Bayesian Expectation Maximization-based Target Localization)算法.VBEM-TL算法先利用一阶泰勒级数展开算法建立稀疏近似模型,然后将目标定位问题转化成稀疏恢复问题,再利用VBEM算法重构稀疏矢量.最后,依据重构的稀疏矢量估计目标位置.实验数据表明,提出的VBEM-TL算法能够有效地降低定位误差.     

基于压缩感知的区域离散化矿井目标定位方法

针对电磁波测距定位方法受井下电磁干扰导致定位精度低,指纹定位方法离线构建指纹特征库面临海量离线数据连续测量和存储的问题,提出了基于压缩感知的区域离散化矿井目标定位方法。首先对定位区域划分网格进行离散化处理,离线测量网格处信号强度,构建指纹特征库;然后将在线采样的少量信号强度通过压缩感知得到包含目标位置信息的稀疏位置矩阵,从而估计目标可能存在的位置;最后通过网格质心法对目标精确定位。实验结果表明,该方法提高了定位精度、缩短了定位时间,实现了矿井目标精确定位。     

压缩感知下的自适应声源定位估计

声源定位是一个应用非常广泛的研究课题。针对阵列定位精度不高的问题,提出一种基于压缩感知的声源定位算法。通过构建冗余字典,该算法将网络中的多个未知源节点的位置作为一个系数向量,然后采用稀疏贝叶斯学习算法估计声源位置。为了增快算法的运行速度,提出一种有效的多分辨率字典构建方法,并迭代地减小定位空间,提高定位精度。实验结果显示,基于压缩感知的声源定位算法可以改善多源节点的定位能力,且有效地减少所需的传感器节点。此外,与基于子空间的算法比较显示,该算法的性能更优越。     

基于网格投影的超多目标进化算法

针对超多目标优化问题求解困难的问题,研究如何得到收敛性和分布性较优的解集,提出了一种基于网格投影的超多目标进化算法-GPEA。该算法根据决策需求将超多目标优化问题的目标空间进行分解,得到投影维目标空间和自由维目标空间;再将投影维目标空间分割为若干投影格,将自由维目标空间分段成若干自由格。算法在每个投影格上进行种群进化,并根据个体相对投影格的位置采用两测度策略筛选个体。第一测度是对落入到投影格内的个体使用非支配排序和自由维目标空间个体筛选策略,选择收敛性和分布性较优的个体作为候选种群。当落入到投影格内的个体数量不足时,进行第二测度筛选,根据个体相对投影格的距离排队,选择相对较近的个体并入到候选种群中。分析了算法的性能,通过对标准测试函数在不同目标下的求解,实验证明基于网格投影的超多目标进化算法能够有效地求解超多目标优化问题。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。