Loading…

Explicit solutions for some simple decentralized detection problems

A decentralized detection problem is considered in which a number of identical sensors transmit a finite-valued function of their observations to a fusion center which makes a final decision on one of M alternative hypotheses. The authors consider the case in which the number of sensors is large, an...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 1990-03, Vol.26 (2), p.282-292
Main Authors: Polychronopoulos, G., Tsitsiklis, J.N.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c396t-b9083af276b168cfe4cca3dbfe10cd7032a985c98b99559650a5bc292cd859633
cites cdi_FETCH-LOGICAL-c396t-b9083af276b168cfe4cca3dbfe10cd7032a985c98b99559650a5bc292cd859633
container_end_page 292
container_issue 2
container_start_page 282
container_title IEEE transactions on aerospace and electronic systems
container_volume 26
creator Polychronopoulos, G.
Tsitsiklis, J.N.
description A decentralized detection problem is considered in which a number of identical sensors transmit a finite-valued function of their observations to a fusion center which makes a final decision on one of M alternative hypotheses. The authors consider the case in which the number of sensors is large, and they derive (asymptotically) optimal rules for determining the messages of the sensors when the observations are generated from a simple and symmetrical set of discrete distributions. They also consider the tradeoff between the number of sensors and the communication rate of each sensor when there is a constraint on the total communication rate from the sensors to the fusion center. The results suggest that it is preferable to have several independent sensors transmitting low-rate (coarse) information instead of a few sensors transmitting high-rate (very detailed) information. They also suggest that an M-ary hypothesis testing problem can be viewed as a collection of M(M-1)/2 binary hypothesis testing problems. From this point of view the most useful messages (decision rules) are those that provide information to the fusion center that is relevant to the largest possible numbers of these binary hypothesis testing problems.< >
doi_str_mv 10.1109/7.53441
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_28668804</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>53441</ieee_id><sourcerecordid>28668804</sourcerecordid><originalsourceid>FETCH-LOGICAL-c396t-b9083af276b168cfe4cca3dbfe10cd7032a985c98b99559650a5bc292cd859633</originalsourceid><addsrcrecordid>eNqFkE1LxDAQhoMouK7i2VsPoqeuSdOkmaMs6wcseNFzSadTiKTtmnRB_fW2u4sePQ0P8_AO8zJ2KfhCCA53xULJPBdHbCaUKlLQXB6zGefCpJApccrOYnwfMTe5nLHl6nPjHbohib3fDq7vYtL0YaSWkujajaekJqRuCNa7b6pHGggnMdmEvvLUxnN20lgf6eIw5-ztYfW6fErXL4_Py_t1ihL0kFbAjbRNVuhKaIMN5YhW1lVDgmNdcJlZMArBVABKgVbcqgozyLA2I0o5Zzf73PHwx5biULYuInlvO-q3scyAj98q-F80WhvD8_9FxcGAmMTbvYihjzFQU26Ca234KgUvp9rLotzVPprXh0gb0fom2A5d_NUV1wDF9MvVXnNE9LfdRfwA3amJJg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>25098914</pqid></control><display><type>article</type><title>Explicit solutions for some simple decentralized detection problems</title><source>IEEE Xplore (Online service)</source><creator>Polychronopoulos, G. ; Tsitsiklis, J.N.</creator><creatorcontrib>Polychronopoulos, G. ; Tsitsiklis, J.N.</creatorcontrib><description>A decentralized detection problem is considered in which a number of identical sensors transmit a finite-valued function of their observations to a fusion center which makes a final decision on one of M alternative hypotheses. The authors consider the case in which the number of sensors is large, and they derive (asymptotically) optimal rules for determining the messages of the sensors when the observations are generated from a simple and symmetrical set of discrete distributions. They also consider the tradeoff between the number of sensors and the communication rate of each sensor when there is a constraint on the total communication rate from the sensors to the fusion center. The results suggest that it is preferable to have several independent sensors transmitting low-rate (coarse) information instead of a few sensors transmitting high-rate (very detailed) information. They also suggest that an M-ary hypothesis testing problem can be viewed as a collection of M(M-1)/2 binary hypothesis testing problems. From this point of view the most useful messages (decision rules) are those that provide information to the fusion center that is relevant to the largest possible numbers of these binary hypothesis testing problems.&lt; &gt;</description><identifier>ISSN: 0018-9251</identifier><identifier>EISSN: 1557-9603</identifier><identifier>DOI: 10.1109/7.53441</identifier><identifier>CODEN: IEARAX</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Aerospace testing ; Applied sciences ; Detection, estimation, filtering, equalization, prediction ; Error analysis ; Exact sciences and technology ; Fusion power generation ; Information, signal and communications theory ; Nonlinear equations ; Performance loss ; Probability ; Random variables ; Sensor fusion ; Sensor systems ; Signal and communications theory ; Signal, noise ; System testing ; Telecommunications and information theory</subject><ispartof>IEEE transactions on aerospace and electronic systems, 1990-03, Vol.26 (2), p.282-292</ispartof><rights>1992 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-b9083af276b168cfe4cca3dbfe10cd7032a985c98b99559650a5bc292cd859633</citedby><cites>FETCH-LOGICAL-c396t-b9083af276b168cfe4cca3dbfe10cd7032a985c98b99559650a5bc292cd859633</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/53441$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=5069973$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Polychronopoulos, G.</creatorcontrib><creatorcontrib>Tsitsiklis, J.N.</creatorcontrib><title>Explicit solutions for some simple decentralized detection problems</title><title>IEEE transactions on aerospace and electronic systems</title><addtitle>T-AES</addtitle><description>A decentralized detection problem is considered in which a number of identical sensors transmit a finite-valued function of their observations to a fusion center which makes a final decision on one of M alternative hypotheses. The authors consider the case in which the number of sensors is large, and they derive (asymptotically) optimal rules for determining the messages of the sensors when the observations are generated from a simple and symmetrical set of discrete distributions. They also consider the tradeoff between the number of sensors and the communication rate of each sensor when there is a constraint on the total communication rate from the sensors to the fusion center. The results suggest that it is preferable to have several independent sensors transmitting low-rate (coarse) information instead of a few sensors transmitting high-rate (very detailed) information. They also suggest that an M-ary hypothesis testing problem can be viewed as a collection of M(M-1)/2 binary hypothesis testing problems. From this point of view the most useful messages (decision rules) are those that provide information to the fusion center that is relevant to the largest possible numbers of these binary hypothesis testing problems.&lt; &gt;</description><subject>Aerospace testing</subject><subject>Applied sciences</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Error analysis</subject><subject>Exact sciences and technology</subject><subject>Fusion power generation</subject><subject>Information, signal and communications theory</subject><subject>Nonlinear equations</subject><subject>Performance loss</subject><subject>Probability</subject><subject>Random variables</subject><subject>Sensor fusion</subject><subject>Sensor systems</subject><subject>Signal and communications theory</subject><subject>Signal, noise</subject><subject>System testing</subject><subject>Telecommunications and information theory</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1990</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LxDAQhoMouK7i2VsPoqeuSdOkmaMs6wcseNFzSadTiKTtmnRB_fW2u4sePQ0P8_AO8zJ2KfhCCA53xULJPBdHbCaUKlLQXB6zGefCpJApccrOYnwfMTe5nLHl6nPjHbohib3fDq7vYtL0YaSWkujajaekJqRuCNa7b6pHGggnMdmEvvLUxnN20lgf6eIw5-ztYfW6fErXL4_Py_t1ihL0kFbAjbRNVuhKaIMN5YhW1lVDgmNdcJlZMArBVABKgVbcqgozyLA2I0o5Zzf73PHwx5biULYuInlvO-q3scyAj98q-F80WhvD8_9FxcGAmMTbvYihjzFQU26Ca234KgUvp9rLotzVPprXh0gb0fom2A5d_NUV1wDF9MvVXnNE9LfdRfwA3amJJg</recordid><startdate>19900301</startdate><enddate>19900301</enddate><creator>Polychronopoulos, G.</creator><creator>Tsitsiklis, J.N.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7TB</scope><scope>FR3</scope><scope>H8D</scope></search><sort><creationdate>19900301</creationdate><title>Explicit solutions for some simple decentralized detection problems</title><author>Polychronopoulos, G. ; Tsitsiklis, J.N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-b9083af276b168cfe4cca3dbfe10cd7032a985c98b99559650a5bc292cd859633</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1990</creationdate><topic>Aerospace testing</topic><topic>Applied sciences</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Error analysis</topic><topic>Exact sciences and technology</topic><topic>Fusion power generation</topic><topic>Information, signal and communications theory</topic><topic>Nonlinear equations</topic><topic>Performance loss</topic><topic>Probability</topic><topic>Random variables</topic><topic>Sensor fusion</topic><topic>Sensor systems</topic><topic>Signal and communications theory</topic><topic>Signal, noise</topic><topic>System testing</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Polychronopoulos, G.</creatorcontrib><creatorcontrib>Tsitsiklis, J.N.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><jtitle>IEEE transactions on aerospace and electronic systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Polychronopoulos, G.</au><au>Tsitsiklis, J.N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Explicit solutions for some simple decentralized detection problems</atitle><jtitle>IEEE transactions on aerospace and electronic systems</jtitle><stitle>T-AES</stitle><date>1990-03-01</date><risdate>1990</risdate><volume>26</volume><issue>2</issue><spage>282</spage><epage>292</epage><pages>282-292</pages><issn>0018-9251</issn><eissn>1557-9603</eissn><coden>IEARAX</coden><abstract>A decentralized detection problem is considered in which a number of identical sensors transmit a finite-valued function of their observations to a fusion center which makes a final decision on one of M alternative hypotheses. The authors consider the case in which the number of sensors is large, and they derive (asymptotically) optimal rules for determining the messages of the sensors when the observations are generated from a simple and symmetrical set of discrete distributions. They also consider the tradeoff between the number of sensors and the communication rate of each sensor when there is a constraint on the total communication rate from the sensors to the fusion center. The results suggest that it is preferable to have several independent sensors transmitting low-rate (coarse) information instead of a few sensors transmitting high-rate (very detailed) information. They also suggest that an M-ary hypothesis testing problem can be viewed as a collection of M(M-1)/2 binary hypothesis testing problems. From this point of view the most useful messages (decision rules) are those that provide information to the fusion center that is relevant to the largest possible numbers of these binary hypothesis testing problems.&lt; &gt;</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/7.53441</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0018-9251
ispartof IEEE transactions on aerospace and electronic systems, 1990-03, Vol.26 (2), p.282-292
issn 0018-9251
1557-9603
language eng
recordid cdi_proquest_miscellaneous_28668804
source IEEE Xplore (Online service)
subjects Aerospace testing
Applied sciences
Detection, estimation, filtering, equalization, prediction
Error analysis
Exact sciences and technology
Fusion power generation
Information, signal and communications theory
Nonlinear equations
Performance loss
Probability
Random variables
Sensor fusion
Sensor systems
Signal and communications theory
Signal, noise
System testing
Telecommunications and information theory
title Explicit solutions for some simple decentralized detection problems
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-21T07%3A55%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Explicit%20solutions%20for%20some%20simple%20decentralized%20detection%20problems&rft.jtitle=IEEE%20transactions%20on%20aerospace%20and%20electronic%20systems&rft.au=Polychronopoulos,%20G.&rft.date=1990-03-01&rft.volume=26&rft.issue=2&rft.spage=282&rft.epage=292&rft.pages=282-292&rft.issn=0018-9251&rft.eissn=1557-9603&rft.coden=IEARAX&rft_id=info:doi/10.1109/7.53441&rft_dat=%3Cproquest_cross%3E28668804%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c396t-b9083af276b168cfe4cca3dbfe10cd7032a985c98b99559650a5bc292cd859633%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=25098914&rft_id=info:pmid/&rft_ieee_id=53441&rfr_iscdi=true