Low-Dimensional Topology of Information Fusion

Daniel Moskovich; Avishy Y. Carmi

doi:10.4108/icst.bict.2014.258005

Low-Dimensional Topology of Information Fusion

Daniel Moskovich, Avishy Y. Carmi

Department of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We provide an axiomatic characterization of information fusion, on the basis of which we define an information fusion network. Our construction is reminiscent of tangle diagrams in low dimensional topology. Information fusion networks come equipped with a natural notion of equivalence. Equivalent networks 'contain the same information', but differ locally. When fusing streams of information, an information fusion network may adaptively optimize itself inside its equivalence class. This provides a fault tolerance mechanism for such networks.

Original language	English
Title of host publication	Proceedings of the 8th International Conference on Bioinspired Information and Communications Technologies
Editors	Jun Suzuki, Tadashi Nakano
Publisher	ACM
Pages	251–258
ISBN (Print)	9781631900532
DOIs	https://doi.org/10.4108/icst.bict.2014.258005
State	Published - Feb 2015

Keywords

reidemeister moves
covariance intersection
fault tolerance
information fusion
adaptive sensor networks
tangle diagrams
information entropy
estimation theory

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10.4108/icst.bict.2014.258005

Cite this

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title = "Low-Dimensional Topology of Information Fusion",

abstract = "We provide an axiomatic characterization of information fusion, on the basis of which we define an information fusion network. Our construction is reminiscent of tangle diagrams in low dimensional topology. Information fusion networks come equipped with a natural notion of equivalence. Equivalent networks 'contain the same information', but differ locally. When fusing streams of information, an information fusion network may adaptively optimize itself inside its equivalence class. This provides a fault tolerance mechanism for such networks.",

keywords = "reidemeister moves, covariance intersection, fault tolerance, information fusion, adaptive sensor networks, tangle diagrams, information entropy, estimation theory",

author = "Daniel Moskovich and Carmi, {Avishy Y.}",

year = "2015",

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editor = "Suzuki, {Jun } and Nakano, {Tadashi }",

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publisher = "ACM",

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AU - Carmi, Avishy Y.

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N2 - We provide an axiomatic characterization of information fusion, on the basis of which we define an information fusion network. Our construction is reminiscent of tangle diagrams in low dimensional topology. Information fusion networks come equipped with a natural notion of equivalence. Equivalent networks 'contain the same information', but differ locally. When fusing streams of information, an information fusion network may adaptively optimize itself inside its equivalence class. This provides a fault tolerance mechanism for such networks.

AB - We provide an axiomatic characterization of information fusion, on the basis of which we define an information fusion network. Our construction is reminiscent of tangle diagrams in low dimensional topology. Information fusion networks come equipped with a natural notion of equivalence. Equivalent networks 'contain the same information', but differ locally. When fusing streams of information, an information fusion network may adaptively optimize itself inside its equivalence class. This provides a fault tolerance mechanism for such networks.

KW - reidemeister moves

KW - covariance intersection

KW - fault tolerance

KW - information fusion

KW - adaptive sensor networks

KW - tangle diagrams

KW - information entropy

KW - estimation theory

U2 - 10.4108/icst.bict.2014.258005

DO - 10.4108/icst.bict.2014.258005

M3 - Conference contribution

SN - 9781631900532

SP - 251

EP - 258

BT - Proceedings of the 8th International Conference on Bioinspired Information and Communications Technologies

A2 - Suzuki, Jun

A2 - Nakano, Tadashi

PB - ACM

ER -

Low-Dimensional Topology of Information Fusion

Abstract

Keywords

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