Graphs for small multiprocessor interconnection networks

Cvetković, Dragoš; Davidović, Tatjana; Ilić, Aleksandar; Simić, Slavko

doi:10.1016/j.amc.2010.07.058

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“…In addition, these integral eigenvectors can be selected so that they contain a lot of coordinates equal to 0 [30].…”

Section: Integral Graphsmentioning

confidence: 99%

Graph spectral techniques in computer sciences

Arsić

Cvetković

Simić

et al. 2012

APPL ANAL DISCRETE M

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We give a survey of graph spectral techniques used in computer sciences. The survey consists of a description of particular topics from the theory of graph spectra independently of the areas of Computer science in which they are used. We have described the applications of some important graph eigenvalues (spectral radius, algebraic connectivity, the least eigenvalue etc.), eigenvectors (principal eigenvector, Fiedler eigenvector and other), spectral reconstruction problems, spectra of random graphs, Hoffman polynomial, integral graphs etc. However, for each described spectral technique we indicate the fields in which it is used (e.g. in modelling and searching Internet, in computer vision, pattern recognition, data mining, multiprocessor systems, statistical databases, and in several other areas). We present some novel mathematical results (related to clustering and the Hoffman polynomial) as well.

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“…In addition, these integral eigenvectors can be selected so that they contain a lot of coordinates equal to 0 [30].…”

Section: Integral Graphsmentioning

confidence: 99%