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Consistency Analysis for Data Fusion: Determining When the Unknown Correlation Can Be Ignored

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Date

2013

Authors

Amirsadri, Ashkan
Bishop, Adrian
Kim, Jonghyuk
Trumpf, Jochen
Petersson, Lars

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE

Abstract

In this paper we examine the conditions in which data fusion can be performed by neglecting the unmodeled correlation between two information sources without compromising the consistency of the system. More specifically, we explore those situations in whi

Description

Keywords

Citation

URI

http://hdl.handle.net/1885/81246

Collections

ANU Research Publications

Source

2013 International Conference on Control, Automation and Information Sciences, ICCAIS 2013

Type

Conference paper

Book Title

Entity type

Access Statement

License Rights

DOI

10.1109/ICCAIS.2013.6720537

Restricted until

2037-12-31

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01_Amirsadri_Consistency_Analysis_for_Data_2013.pdf (629.6 KB)

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