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Component-based quadratic similarity identification for multivariate Gaussian sources
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0002-7807-5681
2018 (English)In: Data Compression Conference Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2018Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers the problem of compression for similarity identification. Unlike classic compression problems, the focus is not on reconstructing the original data. Instead, compression is determined by the reliability of answering given queries. The problem is characterized by the identification rate of a source which is the minimum compression rate which allows reliable answers for a given similarity threshold. In this work, we investigate the component-based quadratic similarity identification for multivariate Gaussian sources. The decorrelated original data is processed by a distinct D- A dmissible system for each component. For a special case, we characterize the component-based identification rate for a correlated Gaussian source. Furthermore, we derived the optimal bit allocation for a given total rate constraint.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2018.
Keywords [en]
Bit allocation, Similarity identification, Gaussian distribution, Component based, Compression rates, Gaussian sources, Identification rates, Optimal bit allocation, Rate constraints, Similarity threshold, Data compression
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-238074DOI: 10.1109/DCC.2018.00086Scopus ID: 2-s2.0-85050969530ISBN: 9781538648834 (print)OAI: oai:DiVA.org:kth-238074DiVA, id: diva2:1278561
Conference
2018 Data Compression Conference, DCC 2018, 27 March 2018 through 30 March 2018
Note

Conference code: 138136; Export Date: 30 October 2018; Conference Paper; CODEN: DDCCF

QC 20180114

Available from: 2019-01-14 Created: 2019-01-14 Last updated: 2019-01-14Bibliographically approved

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Wu, HanweiFlierl, Markus

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf