Importance sampling for error event analysis of HMM frequency line trackers
This paper considers the problem of designing efficient and systematic importance sampling (IS) schemes for the performance study of hidden Markov model (HMM) based trackers. Importance sampling (IS) is a powerful Monte Carlo (MC) variance reduction technique, which can require orders of magnitude f...
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| Veröffentlicht in: | IEEE transactions on signal processing 2002-02, Vol.50 (2), p.411-424 |
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| container_title | IEEE transactions on signal processing |
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| creator | Arulampalam, M.S. Evans, R.J. Letaief, K.B. |
| description | This paper considers the problem of designing efficient and systematic importance sampling (IS) schemes for the performance study of hidden Markov model (HMM) based trackers. Importance sampling (IS) is a powerful Monte Carlo (MC) variance reduction technique, which can require orders of magnitude fewer simulation trials than ordinary MC to obtain the same specified precision. We present an IS technique applicable to error event analysis of HMM based trackers. Specifically, we use conditional IS to extend our work in another of our paper to estimate average error event probabilities. In addition, we derive upper bounds on these error probabilities, which are then used to verify the simulations. The power and accuracy of the proposed method is illustrated by application to an HMM frequency tracker. |
| doi_str_mv | 10.1109/78.978395 |
| format | Article |
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Importance sampling (IS) is a powerful Monte Carlo (MC) variance reduction technique, which can require orders of magnitude fewer simulation trials than ordinary MC to obtain the same specified precision. We present an IS technique applicable to error event analysis of HMM based trackers. Specifically, we use conditional IS to extend our work in another of our paper to estimate average error event probabilities. In addition, we derive upper bounds on these error probabilities, which are then used to verify the simulations. The power and accuracy of the proposed method is illustrated by application to an HMM frequency tracker.</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/78.978395</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithm design and analysis ; Computational modeling ; Computer simulation ; Discrete event simulation ; Error analysis ; Error probability ; Errors ; Estimates ; Frequency ; Hidden Markov models ; Importance sampling ; Mathematical models ; Monte Carlo methods ; Performance analysis ; Signal processing algorithms ; Upper bounds</subject><ispartof>IEEE transactions on signal processing, 2002-02, Vol.50 (2), p.411-424</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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The power and accuracy of the proposed method is illustrated by application to an HMM frequency tracker.</description><subject>Algorithm design and analysis</subject><subject>Computational modeling</subject><subject>Computer simulation</subject><subject>Discrete event simulation</subject><subject>Error analysis</subject><subject>Error probability</subject><subject>Errors</subject><subject>Estimates</subject><subject>Frequency</subject><subject>Hidden Markov models</subject><subject>Importance sampling</subject><subject>Mathematical models</subject><subject>Monte Carlo methods</subject><subject>Performance analysis</subject><subject>Signal processing algorithms</subject><subject>Upper bounds</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqF0TtPwzAQAOAIgUQpDKxMFgOIIeBX_BhRBbSiFQtIbJFxziglL-wUqf8eR6kYGGA53-k--SxfkpwSfE0I1jdSXWupmM72kgnRnKSYS7Efc5yxNFPy9TA5CmGNMeFci0nyuKi71vemsYCCqbuqbN6Raz0C74f4BU2PTGOqbSgDah2ar1bIefjcQGO3KHJAvTf2A3w4Tg6cqQKc7M5p8nJ_9zybp8unh8XsdplaRmWfFrig2jrKDIOMg5Fv1kghYmktE9TojBTMuKiwUFRDkTkHvOAAnBlgik2Ty_HezrfxHaHP6zJYqCrTQLsJucZSi4xJHeXFn5IqTrDA9H8oKdGaDrPPf8F1u_Hxf0KuFGcaUzGgqxFZ34bgweWdL2vjtznB-bCmXKp8XFO0Z6MtAeDH7ZrftsiMtw</recordid><startdate>20020201</startdate><enddate>20020201</enddate><creator>Arulampalam, M.S.</creator><creator>Evans, R.J.</creator><creator>Letaief, K.B.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | Algorithm design and analysis Computational modeling Computer simulation Discrete event simulation Error analysis Error probability Errors Estimates Frequency Hidden Markov models Importance sampling Mathematical models Monte Carlo methods Performance analysis Signal processing algorithms Upper bounds |
| title | Importance sampling for error event analysis of HMM frequency line trackers |
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