Orthogonal similarity transformation into block‐semiseparable matrices of semiseparability rank k

Very recently, an algorithm, which reduces any symmetric matrix into a semiseparable one of semi‐ separability rank 1 by similar orthogonality transformations, has been proposed by Vandebril, Van Barel and Mastronardi. Partial execution of this algorithm computes a semiseparable matrix whose eigenvalues are the Ritz‐values obtained by the Lanczos' process applied to the original matrix. Also a kind of nested subspace iteration is performed at each step. In this paper, we generalize the above results and propose an algorithm to reduce any symmetric matrix into a similar block‐semiseparable one of semiseparability rank k, with k ∈ ?, by orthogonal similarity transformations. Also in this case partial execution of the algorithm computes a block‐semiseparable matrix whose eigenvalues are the Ritz‐values obtained by the block‐Lanczos' process with k starting vectors, applied to the original matrix. Subspace iteration is performed at each step as well. Copyright © 2005 John Wiley & Sons, Ltd.     

ISOMETRIC AND ALLOMETRIC RELATIONSHIPS BETWEEN LARGE AND SMALL‐SCALE TREE SPACING STUDIES

Abstract Basic differences in the relationship between diameter and height have been observed in small and large trees. Small trees (less than 5 m) have little danger of buckling under their own weight, and diameter is proportional to height. Large trees (greater than 5 m) are at risk of buckling under their own weight and are subject to damage from ice and wind. For large trees, diameter cubed is proportional to height squared. This relationship is suggested by the physics of limits to height of cylinders before they buckle under their own weight and has been shown to hold for large trees. Data from large‐scale spacing studies are compared with data from one‐sixteenth scale small spacing studies to determine the validity of this theory. The impact of scaled spacing on scaled diameters at equivalent scaled heights is examined. Results suggest that trees grown at small scales can be “scaled up” to reflect isometric and allometric relationships of trees grown at large scales.     

Novel Features for Binary Time Series Based on Branch Length Similarity Entropy

Branch length similarity (BLS) entropy is defined in a network consisting of a single node and branches. In this study, we mapped the binary time-series signal to the circumference of the time circle so that the BLS entropy can be calculated for the binary time-series. We obtained the BLS entropy values for “1” signals on the time circle. The set of values are the BLS entropy profile. We selected the local maximum (minimum) point, slope, and inflection point of the entropy profile as the characteristic features of the binary time-series and investigated and explored their significance. The local maximum (minimum) point indicates the time at which the rate of change in the signal density becomes zero. The slope and inflection points correspond to the degree of change in the signal density and the time at which the signal density changes occur, respectively. Moreover, we show that the characteristic features can be widely used in binary time-series analysis by characterizing the movement trajectory of Caenorhabditis elegans. We also mention the problems that need to be explored mathematically in relation to the features and propose candidates for additional features based on the BLS entropy profile.     

基于特征结构相似度的遥感影像融合质量评价指标

在分析现有影像融合评价指标的基础上,根据人眼视觉特性,提出一种基于特征结构相似度的遥感影像融合评价指标.首先从原始影像和融合影像中提取空间特征和光谱特征,然后综合计算空间特征和光谱特征的结构相似度作为评价指标,达到评价影像质量的目的.通过对多种传感器获取的遥感影像进行融合实验,结果表明该客观评价方法与主观评价结果一致,...     

Similarity orbits in the Calkin algebra

Let B(H) be the algebra of all bounded linear operators on a complex separable infinite dimensional Hilbert space H.Denote by π the quotient map of B(H) onto the Calkin algebra A(H).In 1984,Apostol et al.raised the following conjecture:If an operator T on H is not similar to a compact perturbation of a Jordan operator,then the similarity orbit of π(T) in A(H) coincides with the π-image of the similarity orbit of T.In this paper,we investigate the structure of similarity orbits in the Calkin algebra and give...     

基于复杂网络上监督学习方法的研究综述

复杂网络已经成为复杂系统分析问题的通用方法,随着人工智能和机器学习的广泛兴起,越来越多的学者开始关注在复杂网络上进行机器学习。监督学习作为机器学习的一个重要组成部分,本文深入研究和总结了基于复杂网络的监督学习方法。首先,本文分别从复杂网络和监督学习的理论基础入手,明确了相似性函数和相异性函数的概念和测度方法,系统梳理了复杂网络的构建方法,并阐明了监督学习的概念及其在机器学习中的地位。其次,介绍了监督学习的几种常用算法,梳理了各种算法的研究现状。然后,提出了基于复杂网络监督学习方法未来关注方向。最后,说明了基于复杂网络监督学习方法的局限性,为相关学者的研究提供了参考。     

SIMILARITY LAWS AND SCALING OF PENETRATION TESTS

利用球形空腔膨胀理论的响应函数对靶板在弹体撞击下的侵彻进行分析，并基于量纲理论建立了侵彻相似律的一般形式.通过对侵彻混凝土靶的已有实验数据进行分析，得到了不同缩比因子下，无量纲侵彻深度曲线随侵彻速度不同而发生偏转和偏移.考虑到材料的应变率效应和损伤演化，认为几何相似律对混凝土等脆性材料在抗侵彻时不成立，有必要引入材料应变率效应和损伤演化对几何相似律的修正.