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Cognitive fusion for target tracking /

Kyriakides, Ioannis,

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Cognitive fusion for target tracking /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Cognitive fusion for target tracking // Ioannis Kyriakides.
Author:	Kyriakides, Ioannis,
Description:	1 online resource (67 p.)
Subject:	Tracking radar - Mathematics. -
Online resource:	https://portal.igpublish.com/iglibrary/search/MCPB0006495.html
ISBN:	1681736659

Cognitive fusion for target tracking /
Kyriakides, Ioannis,

Cognitive fusion for target tracking /Ioannis Kyriakides. - 1 online resource (67 p.) - Synthesis lectures on algorithms and software in engineering. - Synthesis lectures on algorithms and software in engineering..

Includes bibliographical references and index.

The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources. In addition, the use of heterogeneous sensing nodes provides a diversity of information that also enhances estimation performance. This work reviews cognitive systems and presents a cognitive fusion framework for sequential state estimation using adaptive configuration of heterogeneous sensing nodes and heterogeneous data fusion. This work also provides an application of cognitive fusion to the sequential estimation problem of target tracking using foveal and radar sensors.

Mode of access: World Wide Web.

ISBN: 1681736659Subjects--Topical Terms:

3440568
Tracking radar
--Mathematics.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: TK6580

Dewey Class. No.: 621.3848

Cognitive fusion for target tracking /
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245 1 0 $a Cognitive fusion for target tracking / $c Ioannis Kyriakides.
264 1 $a [San Rafael, California] : $b Morgan & Claypool Publishers, $c 2019.
300 $a 1 online resource (67 p.)
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520 $a The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources. In addition, the use of heterogeneous sensing nodes provides a diversity of information that also enhances estimation performance. This work reviews cognitive systems and presents a cognitive fusion framework for sequential state estimation using adaptive configuration of heterogeneous sensing nodes and heterogeneous data fusion. This work also provides an application of cognitive fusion to the sequential estimation problem of target tracking using foveal and radar sensors.
538 $a Mode of access: World Wide Web.
650 0 $a Tracking radar $x Mathematics. $3 3440568
650 0 $a Bayesian statistical decision theory. $3 551404
650 0 $a Search theory. $3 740418
650 0 $a Multisensor data fusion. $3 581966
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830 0 $a Synthesis lectures on algorithms and software in engineering. $3 3440567
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