Quantization for distributed testing of independence

Minna Chen, Wei Liu, Biao Chen, John Matyjas

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

1 Scopus citations

Abstract

We consider the problem of distributed test of statistical independence under communication constraints. While independence test is frequently encountered in various applications, distributed independence test is particularly useful for events detection in sensor networks: data correlation often occurs among sensor observations in the presence of a target. Focusing on the Gaussian case because of its tractability, we study in this paper the characteristics of optimal scalar quantizers for distributed test of independence where the optimality is in the sense of optimizing the error exponent. We also discuss the optimal quantizer properties for the finite sample regime, i.e., that of directly minimizing the error probability.

Original languageEnglish (US)
Title of host publication13th Conference on Information Fusion, Fusion 2010
StatePublished - Dec 1 2010
Event13th Conference on Information Fusion, Fusion 2010 - Edinburgh, United Kingdom
Duration: Jul 26 2010Jul 29 2010

Publication series

Name13th Conference on Information Fusion, Fusion 2010

Other

Other13th Conference on Information Fusion, Fusion 2010
CountryUnited Kingdom
CityEdinburgh
Period7/26/107/29/10

Keywords

  • Distributed signal processing
  • Sensor networks
  • Test of independence

ASJC Scopus subject areas

  • Information Systems

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  • Cite this

    Chen, M., Liu, W., Chen, B., & Matyjas, J. (2010). Quantization for distributed testing of independence. In 13th Conference on Information Fusion, Fusion 2010 [5712034] (13th Conference on Information Fusion, Fusion 2010).