Data reduction in tandem fusion systems

Shengyu Zhu, Biao Chen

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

Abstract

The sufficiency principle is the guiding principle for data reduction in statistical inference. There has been recent effort in developing the sufficiency principle for decentralized inference with a particular emphasis on the relationship between global sufficiency and local sufficiency. This paper studies the sufficiency based data reduction in tandem fusion systems when quantization is needed. We identify conditions such that it is optimal to implement data reduction using sufficient statistics prior to the quantization. They include the well known case when the data at decentralized nodes are conditionally independent as well as a class of problems with conditionally dependent data.

Original languageEnglish (US)
Title of host publication2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings
Pages602-606
Number of pages5
DOIs
StatePublished - Dec 11 2013
Event2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Beijing, China
Duration: Jul 6 2013Jul 10 2013

Publication series

Name2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings

Other

Other2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013
CountryChina
CityBeijing
Period7/6/137/10/13

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Keywords

  • Data reduction
  • quantization
  • sufficiency principle
  • sufficient statistic
  • tandem fusion

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

Cite this

Zhu, S., & Chen, B. (2013). Data reduction in tandem fusion systems. In 2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings (pp. 602-606). [6625412] (2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings). https://doi.org/10.1109/ChinaSIP.2013.6625412