人脸识别中适合于小样本情况下的监督化拉普拉斯判别分析

提取有效特征对高维数据的模式分类起着关键的作用.无监督判别投影,通过最大化非局部散度和局部散度之比,在数据降维和特征提取上表现出较好的性能,但是它是一种非监督学习算法,并且存在小样本问题.针对这些问题,提出了监督化拉普拉斯判别分析,算法在考虑非局部散度和局部散度时考虑了样本的类别信息;通过丢弃总体拉普拉斯散度矩阵的零空间,并将类内拉普拉斯散度矩阵投影到总体拉普拉斯散度矩阵的主空间中,然后在该空间中进行特征问题的求解,从而避免了小样本问题.通过理论分析,该算法没有任何判别信息损失,同时在计算上效率也较高.在人脸识别上的实验验证了算法的正确性和有效性.     

改进的线性判别分析及人脸识别

为有效解决传统LDA（线性鉴别分析）的小样本规模问题,提出一种改进的LDA算法。首先对样本进行无损降维;然后在Fisher准则基础上,用散度矩阵差代替散度矩阵的比值,避免对类内矩阵求逆的同时也降低了计算复杂度,实现有效的特征抽取;最后实现对人脸的识别。实验结果表明,该算法是有效的,优于传统LDA方法。     

小波核局部Fisher判别分析的高光谱遥感影像特征提取

为了提高高光谱遥感影像的分类精度,充分利用影像的光谱和局部信息,文中提出小波核局部Fisher判别分析的高光谱遥感影像特征提取方法.通过小波核函数将数据集从低维原始空间映射至高维特征空间,考虑到数据的局部信息,利用加权矩阵计算散度矩阵,对局部Fisher判别准则函数求解最优特征矩阵,使不同类别的样本在高维特征空间中的可分离性更佳.在2个公开高光谱数据集上的实验表明,文中方法的总体分类精度和Kappa系数都有所提高.     

完备正交邻域保持判别嵌入的人脸识别

为解决邻域保持判别嵌入算法所面临的小样本问题,并充分利用类内邻域散度矩阵零空间和非零空间中的判别信息进行人脸识别,提出一种完备正交邻域保持判别嵌入的人脸识别算法。首先间接地利用特征分解方法去除总体邻域散度矩阵的零空间;然后分别在类内邻域散度矩阵零空间和非零空间中提取最优判别矢量。此外,为进一步提高算法的识别性能,给出了基于瘦QR分解的正交投影矩阵的求解方法。在ORL和Yale人脸库上验证了以上算法的有效性。     

利用标准化LDA进行人脸识别

线性判别分析（LDA）是一种较为普遍的用于特征提取的线性分类方法。提出一种基于LDA的人脸识别方法－－标准化LDA，该方法克服了传统LDA方法的缺点，重新定义了样本类间离散度矩阵，在原始定义的基础上增加一个由类间距离决定的可变权函数，使得在选择投地，能够更好地分开各个类的样本；同时，它采用一种合理而有效的方法解决矩阵奇异的问题，即保留样本类内离散度矩阵的零空间，因为这个空间包含了最具有判别能力的信息。在这个零空间里，寻找对应于样本类间离散度矩阵的较大特征值的特征向量作为最后降维的转换矩阵。实验结果显示，在人脸识别中，与传统LDA相比，该方法有更好的识别率。标准化LDA也可以用于其他图像识别问题。     

核零空间线性鉴别分析及其在人脸识别中的应用

零空间线性鉴别分析NLDA充分利用样本总类内离散度矩阵的零空间信息,能有效克服线性鉴别分析LDA的小样本问题.核方法通过非线性映射,将输入空间样本映射到高维特征空间,再在高维特征空间利用线性特征提取算法.因此,核方法属于非线性特征提取算法.文中结合LDA、NLDA和核方法的优点,引入了核零空间线性鉴别分析KNLDA,导出了KNLDA算法.该算法通过引入核函数,得到低维矩阵,有效避免了直接计算复杂的非线性映射函数,解决了高维类内离散度矩阵的维数灾难问题.同时,将KNLDA算法应用于人脸识别.基于ORL人脸数据库以及ORL与Yale混合人脸数据库的实验结果表明了KNLDA算法的有效性.     

基于2D-PCA的两级LDA人脸识别方法

线性鉴别分析(LDA)小样本问题的已有解决方法在构造最优投影子空间时未完整利用LDA的4个信息空间,为此,提出一种基于二维主成分分析(2D-PCA)的两级LDA人脸识别方法。采用减法运算对样本类内散度矩阵和类间散度矩阵的特征值矩阵求逆,以解决小样本问题,并连续应用Fisher准则和修改后的Fisher准则连接2个投影子空间,获取包含LDA的4个信息空间的最优投影方向,利用2D-PCA对输入样本做预处理,以减少计算复杂度。在ORL和YALE人脸库上的实验结果表明,该方法虽然训练时间略有增加,但识别率分别为92.5%和95.8%,优于其他常用LDA算法。     

I-VLDNS:一种改进的线性判别子空间模式识别算法

针对现有模式判别分析方法中普遍存在的子空间优化与"小样本"问题,首先剖析总体、类内以及类间三种散布矩阵的零空间的物理含义,深入阐释有效零空间与有效线性判别零空间核心原理;其次,研究始空间中总体、类间散布矩阵与有效零空间、有效值域空间上的总体、类间散布矩阵关于特征值与特征向量之间的关联关系,并且获取类内散布矩阵零空间、值域空间上关于Fisher线性判别率的关键结论;最后,基于有效线性判别零空间理论,设计出一种改进的线性判别子空间模式识别算法,即I-VLDNS。通过相关数据集模拟实验表明,I-VLDNS算法在模式识别分析性能、精确度以及鲁棒性上均得到进一步优化与提高。     

文本分类中基于散度差的线性特征抽取方法

分析了特征选择与特征抽取的特点与不足,针对Fisher线性鉴别准则存在问题,在一种加权散度差线性鉴别准则的基础上提出了一种基于散度差与SVD相结合的文本特征抽取方法.在解决了类内散布矩阵Sw的奇异性问题困扰同时,通过对低阶矩阵的奇异值分解取代了对高阶矩阵的特征值求解,计算量大大减少.在最低限度减少信息损失的前提下实现了特征维数的大幅度减缩.试验结果表明,这种方法在文本分类上的准确性较好.     

一种改进的线性判别分析算法MLDA

线性判别分析(LDA)是模式识别方法之一,已广泛应用于模式识别、数据分析等诸多领域。线性判别分析法寻找的是有效分类的方向。而当样本维数远大于样本个数(即小样本问题)时,LDA便束手无策。为有效解决线性判别分析法的小样本问题,提出了一种改进的LDA算法——MLDA。该算法将类内离散度矩阵进行标量化处理,有效地避免了对类内离散度矩阵求逆。通过实验证明MLDA在一定程度上解决了经典LDA的小样本问题。     

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。     

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.