Error event simulation for HMM tracking algorithms using importance sampling
Importance sampling is a technique for speeding up Monte Carlo (MC) simulations. The fundamental idea is to use a different simulation distribution to increase the relative frequency of "important" events and then weight the observed data in order to obtain an unbiased estimate of the para...
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| Veröffentlicht in: | IEEE transactions on signal processing 1998-03, Vol.46 (3), p.720-736 |
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| container_end_page | 736 |
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| container_title | IEEE transactions on signal processing |
| container_volume | 46 |
| creator | Arulampalam, M.S. Evans, R.J. Letaief, K.B. |
| description | Importance sampling is a technique for speeding up Monte Carlo (MC) simulations. The fundamental idea is to use a different simulation distribution to increase the relative frequency of "important" events and then weight the observed data in order to obtain an unbiased estimate of the parameter of interest. This estimate often requires orders-of-magnitude fewer simulation trials than ordinary MC simulations to obtain the same specified precision. We present an importance sampling technique applicable to error event simulation of hidden Markov model (HMM) tracking algorithms. The computational savings possible with the use of this technique are demonstrated both analytically and using simulation results for a specific HMM tracking algorithm. |
| doi_str_mv | 10.1109/78.661338 |
| format | Article |
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The computational savings possible with the use of this technique are demonstrated both analytically and using simulation results for a specific HMM tracking algorithm.</description><subject>Analytical models</subject><subject>Applied sciences</subject><subject>Computational Intelligence Society</subject><subject>Computational modeling</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Digital communication</subject><subject>Discrete event simulation</subject><subject>Exact sciences and technology</subject><subject>Frequency estimation</subject><subject>Hidden Markov models</subject><subject>Information, signal and communications theory</subject><subject>Monte Carlo methods</subject><subject>Parameter estimation</subject><subject>Signal and communications theory</subject><subject>Signal, noise</subject><subject>Standards development</subject><subject>Telecommunications and information theory</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kM1LxDAQxYMouK4evHrqQQQPXTNJm7RHWVZX2MWLgreSppM1mn6YtIL_vV267GmGN7958B4h10AXADR_kNlCCOA8OyEzyBOIaSLF6bjTlMdpJj_OyUUIX5RCkuRiRjYr71sf4S82fRRsPTjV27aJzCiut9uo90p_22YXKbdrve0_6xANYS_Yumt9rxqNUVB150btkpwZ5QJeHeacvD-t3pbrePP6_LJ83MSaU9HHgFVZybLUVa4M1QBodGJKkRtdUloZNBVDybngMjEp5wpKyrhIKsi5SEHwObmbfDvf_gwY-qK2QaNzqsF2CAXLUpGxTI7g_QRq34bg0RSdt7XyfwXQYt9XIbNi6mtkbw-mKmjljB-j2XB8YIxCztiI3UyYRcTj9eDxD4Ifc2E</recordid><startdate>19980301</startdate><enddate>19980301</enddate><creator>Arulampalam, M.S.</creator><creator>Evans, R.J.</creator><creator>Letaief, K.B.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19980301</creationdate><title>Error event simulation for HMM tracking algorithms using importance sampling</title><author>Arulampalam, M.S. ; Evans, R.J. ; Letaief, K.B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c306t-1edbd7bbcd9af0c11efc4fb69fcb00dfefd2e7336374f533a1b02364d19365163</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Analytical models</topic><topic>Applied sciences</topic><topic>Computational Intelligence Society</topic><topic>Computational modeling</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Digital communication</topic><topic>Discrete event simulation</topic><topic>Exact sciences and technology</topic><topic>Frequency estimation</topic><topic>Hidden Markov models</topic><topic>Information, signal and communications theory</topic><topic>Monte Carlo methods</topic><topic>Parameter estimation</topic><topic>Signal and communications theory</topic><topic>Signal, noise</topic><topic>Standards development</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Arulampalam, M.S.</creatorcontrib><creatorcontrib>Evans, R.J.</creatorcontrib><creatorcontrib>Letaief, K.B.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems 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><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Arulampalam, M.S.</au><au>Evans, R.J.</au><au>Letaief, K.B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Error event simulation for HMM tracking algorithms using importance sampling</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>1998-03-01</date><risdate>1998</risdate><volume>46</volume><issue>3</issue><spage>720</spage><epage>736</epage><pages>720-736</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>Importance sampling is a technique for speeding up Monte Carlo (MC) simulations. 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| ispartof | IEEE transactions on signal processing, 1998-03, Vol.46 (3), p.720-736 |
| issn | 1053-587X 1941-0476 |
| language | eng |
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| subjects | Analytical models Applied sciences Computational Intelligence Society Computational modeling Detection, estimation, filtering, equalization, prediction Digital communication Discrete event simulation Exact sciences and technology Frequency estimation Hidden Markov models Information, signal and communications theory Monte Carlo methods Parameter estimation Signal and communications theory Signal, noise Standards development Telecommunications and information theory |
| title | Error event simulation for HMM tracking algorithms using importance sampling |
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