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Cognitive fusion for target tracking /

Kyriakides, Ioannis,

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 radarMathematics.
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:

214112
Tracking radar
--Mathematics.Index Terms--Genre/Form:

214472
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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490 1 $a Synthesis lectures on algorithms and software in engineering
504 $a Includes bibliographical references and index.
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 214112
650 0 $a Bayesian statistical decision theory. $3 182005
650 0 $a Search theory. $3 211960
650 0 $a Multisensor data fusion. $3 182455
655 4 $a Electronic books. $2 local. $3 214472
830 0 $a Synthesis lectures on algorithms and software in engineering. $3 869734
856 4 0 $u https://portal.igpublish.com/iglibrary/search/MCPB0006495.html