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Dense graph / Adjacency matrix / Neighbourhood / Path decomposition / Graph theory / Dense subgraph / Graph


Detection Theory for Graphs Benjamin A. Miller, Nadya T. Bliss, Patrick J. Wolfe, and Michelle S. Beard Graphs are fast emerging as a common data structure used in many scientific and engineering
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Document Date: 2013-10-17 12:48:29


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File Size: 4,41 MB

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Company

12 LINCOLN LABORATORY JOURNAL / Vertex / LINCOLN LABORATORY JOURNAL / /

IndustryTerm

myriad applications / signal processing framework / possible travel routes / recursive algorithm / power-law exponent / identification algorithm / power-law degree distributions / graph processing chain / aforementioned k-means-based clustering algorithm / bank / inverse power-law distribution / social networking / complicated algorithm / k-means-based clustering algorithm / real-world networks / large networks / signal processing chain / detection algorithm / signal processing / detection algorithms / signal processing application domains / power-law background / signal processing theory / /

MarketIndex

FIGURE / /

Organization

Lincoln Laboratory mission / /

Person

Michelle S. Beard Graphs / Nadya T. Bliss / MICHELLE S. BEARD / Benjamin A. Miller / Patrick J. Wolfe / /

Position

representative / analyst / /

Product

L1 / /

ProgrammingLanguage

V / /

Technology

aforementioned k-means-based clustering algorithm / k-means-based clustering algorithm / One detection algorithm / Detection Three algorithms / detection algorithms / second algorithm / Simulation / recursive algorithm / detection algorithm / two algorithms / identification algorithm / /

SocialTag