Performance assessment of sequential Bayesian processors based on probably approximately correct computation and information theory
A novel method to characterise the efficacy and efficiency of different sequential Bayesian processor implementations is proposed. This method is based on concepts of probably approximately correct computation and information theory measures. The proposed approach is used to compare the performance...
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| Published in | Electronics letters Vol. 54; no. 6; pp. 357 - 359 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
The Institution of Engineering and Technology
22.03.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0013-5194 1350-911X 1350-911X |
| DOI | 10.1049/el.2017.4159 |
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| Abstract | A novel method to characterise the efficacy and efficiency of different sequential Bayesian processor implementations is proposed. This method is based on concepts of probably approximately correct computation and information theory measures. The proposed approach is used to compare the performance of three different Bayesian estimation algorithms (particle filter, unscented Kalman filter (UKF), and UKF with outer feedback correction loops) in the context of lithium-ion battery state-of-charge monitoring. |
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| AbstractList | A novel method to characterise the efficacy and efficiency of different sequential Bayesian processor implementations is proposed. This method is based on concepts of probably approximately correct computation and information theory measures. The proposed approach is used to compare the performance of three different Bayesian estimation algorithms (particle filter, unscented Kalman filter (UKF), and UKF with outer feedback correction loops) in the context of lithium‐ion battery state‐of‐charge monitoring. |
| Author | Orchard, M.E Jaras, I |
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| Cites_doi | 10.1214/aoms/1177729330 10.1109/PHM.2008.4711433 10.1198/016214504000000151 10.1109/ASSPCC.2000.882463 10.1109/TCAD.2002.1013889 10.1002/0471200611 10.1007/978-1-4757-3437-9 10.1109/TC.2002.1017694 |
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| Keywords | lithium-ion battery state-of-charge monitoring Bayesian estimation algorithms state estimation performance assessment nonlinear filters information theory Kalman filters sequential Bayesian processors unscented Kalman filter |
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| References | Alippi, C. (C4) 2002; 21 Chernoff, H. (C7) 1952; 23 Vidyasagar, M. (C5) 1998; 7 Pola, D.; Navarrete, H.; Orchard, M. (C10) 2015; 64 Alippi, C. (C6) 2002; 51 Godsill, S.; Doucet, A.; West, M. (C8) 2004; 99 Orchard, M.; Tobar, F.; Vachtsevanos, G. (C12) 2009; 18 2008 1997 2004; 99 1952; 23 1991 2001 1998; 7 2000 2002; 51 2015; 64 2002; 21 2009; 18 e_1_2_7_5_1 e_1_2_7_10_1 e_1_2_7_3_1 Pola D. (e_1_2_7_11_1) 2015; 64 Bai Er‐Wei (e_1_2_7_4_1) 1997 Vidyasagar M. (e_1_2_7_6_1) 1998; 7 e_1_2_7_9_1 e_1_2_7_8_1 e_1_2_7_7_1 Orchard M. (e_1_2_7_13_1) 2009; 18 e_1_2_7_2_1 e_1_2_7_12_1 |
| References_xml | – volume: 51 start-page: 740 year: 2002 end-page: 749 ident: C6 article-title: Randomized algorithms: a system-level, poly-time analysis of robust computation publication-title: Trans. Comput. – volume: 21 start-page: 749 year: 2002 end-page: 762 ident: C4 article-title: A probably approximately correct framework to estimate performance degradation in embedded systems publication-title: Trans. Comput.-Aided Des. Integr. Circuits Syst. – volume: 23 start-page: 493 year: 1952 end-page: 507 ident: C7 article-title: A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations publication-title: Ann. Math. Stat. – volume: 18 start-page: 295 year: 2009 end-page: 304 ident: C12 article-title: Outer feedback correction loops in particle filtering-based prognosis algorithms: statistical performance comparison publication-title: Stud. Inf. Controls – volume: 64 start-page: 1 year: 2015 end-page: 11 ident: C10 article-title: Particle-filtering-based discharge time prognosis for lithium-ion batteries with a statistical characterization of use profiles publication-title: Trans. Reliab. – volume: 99 start-page: 438 year: 2004 end-page: 449 ident: C8 article-title: Monte Carlo smoothing for nonlinear time series publication-title: J. Am. Stat. Assoc. – volume: 7 start-page: 287 year: 1998 end-page: 310 ident: C5 article-title: Statistical learning theory and randomized algorithms for control publication-title: Control Syst. – year: 1997 – year: 2000 – volume: 7 start-page: 287 year: 1998 end-page: 310 article-title: Statistical learning theory and randomized algorithms for control publication-title: Control Syst. – volume: 99 start-page: 438 year: 2004 end-page: 449 article-title: Monte Carlo smoothing for nonlinear time series publication-title: J. Am. Stat. Assoc. – volume: 18 start-page: 295 year: 2009 end-page: 304 article-title: Outer feedback correction loops in particle filtering‐based prognosis algorithms: statistical performance comparison publication-title: Stud. Inf. Controls – volume: 23 start-page: 493 year: 1952 end-page: 507 article-title: A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations publication-title: Ann. Math. Stat. – volume: 51 start-page: 740 year: 2002 end-page: 749 article-title: Randomized algorithms: a system‐level, poly‐time analysis of robust computation publication-title: Trans. Comput. – year: 1991 – volume: 64 start-page: 1 year: 2015 end-page: 11 article-title: Particle‐filtering‐based discharge time prognosis for lithium‐ion batteries with a statistical characterization of use profiles publication-title: Trans. Reliab. – year: 2001 – year: 2008 – volume: 21 start-page: 749 year: 2002 end-page: 762 article-title: A probably approximately correct framework to estimate performance degradation in embedded systems publication-title: Trans. Comput.‐Aided Des. Integr. Circuits Syst. – ident: e_1_2_7_8_1 doi: 10.1214/aoms/1177729330 – ident: e_1_2_7_3_1 doi: 10.1109/PHM.2008.4711433 – volume-title: Worst‐case properties of the uniform distribution and randomized algorithms for robustness analysis year: 1997 ident: e_1_2_7_4_1 – ident: e_1_2_7_9_1 doi: 10.1198/016214504000000151 – ident: e_1_2_7_12_1 doi: 10.1109/ASSPCC.2000.882463 – ident: e_1_2_7_5_1 doi: 10.1109/TCAD.2002.1013889 – ident: e_1_2_7_10_1 doi: 10.1002/0471200611 – ident: e_1_2_7_2_1 doi: 10.1007/978-1-4757-3437-9 – volume: 18 start-page: 295 year: 2009 ident: e_1_2_7_13_1 article-title: Outer feedback correction loops in particle filtering‐based prognosis algorithms: statistical performance comparison publication-title: Stud. Inf. Controls – ident: e_1_2_7_7_1 doi: 10.1109/TC.2002.1017694 – volume: 7 start-page: 287 year: 1998 ident: e_1_2_7_6_1 article-title: Statistical learning theory and randomized algorithms for control publication-title: Control Syst. – volume: 64 start-page: 1 year: 2015 ident: e_1_2_7_11_1 article-title: Particle‐filtering‐based discharge time prognosis for lithium‐ion batteries with a statistical characterization of use profiles publication-title: Trans. Reliab. |
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| SubjectTerms | Bayesian estimation algorithms Information and communications information theory Kalman filters lithium‐ion battery state‐of‐charge monitoring nonlinear filters performance assessment sequential Bayesian processors state estimation unscented Kalman filter |
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| Title | Performance assessment of sequential Bayesian processors based on probably approximately correct computation and information theory |
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