基于鱼群算法的无线传感网簇内信号盲检测

本文在无线传感网传输模型分簇的基础上,针对簇内信号盲检测降低误码率和提高收敛性问题,提出了一种基于人工鱼群算法的信号盲检测算法,所述算法采用自下而上的设计,构造了人工鱼的基本模型以及其各行为的模型,不需要了解问题的特殊信息,只需要对问题解的优劣进行比较,用此模型解决无线传感网簇内盲信号检测的二次规划性能函数。仿真表明,算法具有全局收敛性好、收敛速度快、误码率低的优点,从而成功实现簇内簇首传感器信号盲检测。     

基于Hopfield神经网络的WSN分布式拓扑

提出一种基于Hopfield神经网络模型的传感器网络的分布式广播算法。在已有网络拓扑的基础上对其数据获取方式进行改进。用优化的Hopfield神经网络模型在各簇中分别从广播源点开始遍历所有传感节点,并返回广播源点的最优链路。利用Hopfield神经网络收敛速率快、通信路径最优,且易于硬件电路实现的特点,形成了能量消耗较少、延时较小的WSN网络,它是一种能量高效的网络。     

基于无线传感器网络虚拟MIMO系统盲均衡

无线传感器网络（ Wireless Sensor Network,WSN）是近年来人们研究的热点。针对无线传感器网络高密度分布的特点,在无线传感器网络进行分簇处理的基础上,文中构造了一种新的虚拟MIMO系统模型,并且针对传统的盲均衡算法进行改进,提出一种新的适用于无线传感网的TXK_Z盲均衡算法,最后对该虚拟MIMO系统利用文中提出的TXK_Z算法进行盲均衡的仿真实验。实验表明,跟传统的盲均衡算法相比,在低信噪比、短数据的环境下,改进后算法的误码率明显降低,性能显著提高。     

无线传感网中一种智能数据融合算法的实现及仿真分析

在无线传感网中,传感器节点一般都由自身装配的电池供电,难以进行电量补充,因此节约电量对于无线传感网来说至关重要.为了提高无线传感网能量使用效率,延长网络生存时间,提出了一种结合遗传算法和粒子群算法优化BP神经网络的智能数据融合算法 GAPSOBP(BP Neural Network Data Fusion algorithm optimized by Genetic algorithm and Particle swarm).GAPSOBP算法将无线传感网的节点类比为BP神经网络中的神经元,通过神经网络提取无线传感网采集的感知数据并结合分簇路由对收集的传感数据进行融合处理,从而大幅减少发往汇聚节点的网络数据量.仿真结果表明,与经典LEACH算法和PSOBP算法相比,GAPSOBP算法能有效减少网络通信量,节约节点能量,显著延长网络生存时间.     

利用改进的SUSAN算法优化无线传感网络簇头节点

在LEACH—C算法的基础上,提出了对传统无线传感器网络路由算法的改进,在过去的无线传感网络的路由算法中采用模拟退火算法,来实现选取簇头,改进后的算法应用图像角点检测算子-SUSAN算子,使其在簇头的选取上,定位更准速度更快。改进后的无线传感器网络路由算法能更好地节能,有效地延长了整个无线传感器网络的寿命。     

自适应扰动暂态混沌神经网络MPSK盲检测

为提高MPSK信号盲检测算法的性能,针对CHNN_APHM算法易陷入局部最优的缺点,本文引入暂态混沌神经网络模型,使用新的模拟退火策略,加入扰动因子和混沌,提出带扰动的幅值相位型离散幅值多电平暂态混沌神经网络算法。算法使用暂态混沌神经网络提高抗噪性能,并在起始时刻使用混沌初始化获得原始信号,选取与发送信号相关性高的微小扰动因子使算法跳出局部最优解。实验仿真结果证明,带扰动的幅值相位型离散幅值多电平暂态混沌神经网络MPSK信号盲检测算法需要较少的起点个数,能在更小的信噪比和更短的数据长度下收敛,有效提高了抗干扰性能。     

基于PSO-BP的无线传感器网络数据融合算法研究

为提高无线传感器网络(WSN)数据融合效率,减少网络的通信量以及降低传感网的能量消耗,提出一种基于粒子群优化BP神经网络的无线传感器网络数据融合算法;该算法将粒子群算法优化BP神经网络的权值和阈值后,与传感器网络分簇路由协议有机结合,将无线传感器网络中簇头和节点等同于BP神经网络里的神经元,利用优化后的BP神经网络有效地提取WSN数据融合原始数据之中的少量特征数据,之后把提取的特征数据发送到汇聚节点,进而提升数据融合效率,延长网络生存周期;仿真实验证明,与LEACH算法、BP神经网络和GABP算法相比,该算法可有效减少网络通信量,降低节点总能耗的15%,延长网络生存时间。     

LEACH协议的簇头多跳（LEACH-M）改进算法

节能高效的实现路由转发是路由设计的一个关键点。总结了目前已有的无线传感器网络的传输路由模式,发现早先提出的LEACH协议虽是无线传感网中的低功耗自适应分层路由算法,但会造成簇头节点负载过重。成簇算法是传感器网络中减少能量消耗的一种关键技术。提出的是基于LEACH算法的多跳路由改进算法,并在考虑簇头最优个数的选择下,通过采用簇头之间的多跳算法达到减少能量消耗、延长传感网的寿命的目的。实验表明此方法有效。     

差分算法在盲均衡中的应用与研究

文中给出了基于差分的盲检测算法,并进行了应用与研究,仿真表明差分盲检测算法具有较强的全局收敛能力和鲁棒性,但是易陷入局部最小值,收敛速度较慢,因此文中对差分盲检测算法做了进一步改进,从而得到改进的差分盲检测算法.改进的差分盲检测算法利用了混沌算法的初值敏感性、拓扑传递性、整体稳定性将其与差分盲检测算法相结合,在算法初始化种群时加入混沌扰动,寻找无规律中的有规律.仿真结果表明了改进算法加快了收敛速度,优化了算法性能.     

发明与专利

正用Hopfield神经网络对无线传感器网络分簇的方法申请号:201310112996.0【公开号】CN103167578A【公开日】2013.06.19【分类号】H04W40/02(2009.01)I;H04W84/18(2009.01)I【申请日】2013.04.02【申请人】山东大学【发明人】江铭炎;杨敏【摘要】用Hopfield神经网络对无线传感器网络分簇的方法,属于无线传感器网络技术领域。针对LEACH协议的不足予以改进,使各个簇头的分布与各节点的能量消耗得到均衡,并将此分簇协议建模为组合优化问题。本发明     

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。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.