Ensuring Strong Dominance for the Leading Eigenvalues for Cluster Ensembles

Abstract

Spectral analysis is a popular mathematical tool in analyzing a variety of network and distributed systems. For a special class of networks, called cluster ensembles, which are made of interconnected clusters, we can characterize those which exhibit strong dominance of the leading eigenvalues in terms of the cluster structure. For such systems, only these leading eigenvalues and their corresponding eigenvectors will need to be examined in studying important properties of the underlying system. This paper establishes several bounds on eigenvalue separation ratios in terms of the number of clusters, their sizes and cluster interconnection topologies

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2011
Accession Number
ADA551480

Entities

People

  • Bruce W. Suter
  • H. T. Kung

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Computer Communications
  • Detectors
  • Eigenvalues
  • Eigenvectors
  • Government Employees
  • Governments
  • Inequalities
  • Information Operations
  • Military Research
  • Network Topology
  • Networks
  • Sensor Networks
  • Topology

Fields of Study

  • Physics

Readers

  • Parallel and Distributed Computing.
  • Quantum spin resonance or Electron Paramagnetic Resonance spectroscopy.
  • Strategic Security Studies