Conditional dependence in distributed detection: How far can we go?

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Distributed detection with conditionally independent observations at local sensors is well understood. The problem becomes significantly more complicated when dependence is present among sensor observations. In this paper, we attempt to make progress in our understanding of the dependent observation case. Toward this end, we present a new hierarchical model by introducing a hidden or latent variable; this model attempts to present a unified framework for distributed detection with conditionally dependent or independent observations. By a close examination of this model, we identify a class of distributed detection problems with conditionally dependent observations whose optimal sensor signaling structure resem bles that of the independent case. This class of problems exhibits a decoupling effect on the form of the optimal local decision rules, much in the same way as the conditionally independent case. Important cases of this class of problems include both the previously known Gaussian case under certain parameter regimes as well as several problems first introduced in this paper. An example is given to illustrate the proposed design approach.

Original languageEnglish (US)
Title of host publication2009 IEEE International Symposium on Information Theory, ISIT 2009
Pages664-668
Number of pages5
DOIs
StatePublished - Nov 19 2009
Event2009 IEEE International Symposium on Information Theory, ISIT 2009 - Seoul, Korea, Republic of
Duration: Jun 28 2009Jul 3 2009

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8102

Other

Other2009 IEEE International Symposium on Information Theory, ISIT 2009
CountryKorea, Republic of
CitySeoul
Period6/28/097/3/09

Keywords

  • Dependent observation
  • Distributed detection
  • Hierarchical independence model
  • Quantization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Conditional dependence in distributed detection: How far can we go?'. Together they form a unique fingerprint.

  • Cite this

    Chen, H., Varshney, P. K., & Chen, B. (2009). Conditional dependence in distributed detection: How far can we go? In 2009 IEEE International Symposium on Information Theory, ISIT 2009 (pp. 664-668). [5205665] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2009.5205665