A variance-estimation-based stopping rule for symbolic dynamic filtering

Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state a...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wen, Yicheng [verfasserIn] Ray, Asok Du, Qiang

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2011

Schlagwörter:	Probabilistic finite state automata Markov chains Variance estimation

Anmerkung:	© Springer-Verlag London Limited 2011

Übergeordnetes Werk:	Enthalten in: Signal, image and video processing - London [u.a.] : Springer, 2007, 7(2011), 1 vom: 18. Feb., Seite 189-195
Übergeordnetes Werk:	volume:7 ; year:2011 ; number:1 ; day:18 ; month:02 ; pages:189-195

Links:	Volltext

DOI / URN:	10.1007/s11760-011-0215-y

Katalog-ID:	SPR022266542

Internformat


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520			\|a Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6.
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650		4	\|a Markov chains \|7 (dpeaa)DE-He213
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700	1		\|a Ray, Asok \|4 aut
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912			\|a GBV_ILN_370
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allfields	10.1007/s11760-011-0215-y doi (DE-627)SPR022266542 (SPR)s11760-011-0215-y-e DE-627 ger DE-627 rakwb eng Wen, Yicheng verfasserin aut A variance-estimation-based stopping rule for symbolic dynamic filtering 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2011 Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6. Probabilistic finite state automata (dpeaa)DE-He213 Markov chains (dpeaa)DE-He213 Variance estimation (dpeaa)DE-He213 Ray, Asok aut Du, Qiang aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 7(2011), 1 vom: 18. Feb., Seite 189-195 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:7 year:2011 number:1 day:18 month:02 pages:189-195 https://dx.doi.org/10.1007/s11760-011-0215-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2011 1 18 02 189-195
spelling	10.1007/s11760-011-0215-y doi (DE-627)SPR022266542 (SPR)s11760-011-0215-y-e DE-627 ger DE-627 rakwb eng Wen, Yicheng verfasserin aut A variance-estimation-based stopping rule for symbolic dynamic filtering 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2011 Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6. Probabilistic finite state automata (dpeaa)DE-He213 Markov chains (dpeaa)DE-He213 Variance estimation (dpeaa)DE-He213 Ray, Asok aut Du, Qiang aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 7(2011), 1 vom: 18. Feb., Seite 189-195 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:7 year:2011 number:1 day:18 month:02 pages:189-195 https://dx.doi.org/10.1007/s11760-011-0215-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2011 1 18 02 189-195
allfields_unstemmed	10.1007/s11760-011-0215-y doi (DE-627)SPR022266542 (SPR)s11760-011-0215-y-e DE-627 ger DE-627 rakwb eng Wen, Yicheng verfasserin aut A variance-estimation-based stopping rule for symbolic dynamic filtering 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2011 Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6. Probabilistic finite state automata (dpeaa)DE-He213 Markov chains (dpeaa)DE-He213 Variance estimation (dpeaa)DE-He213 Ray, Asok aut Du, Qiang aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 7(2011), 1 vom: 18. Feb., Seite 189-195 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:7 year:2011 number:1 day:18 month:02 pages:189-195 https://dx.doi.org/10.1007/s11760-011-0215-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2011 1 18 02 189-195
allfieldsGer	10.1007/s11760-011-0215-y doi (DE-627)SPR022266542 (SPR)s11760-011-0215-y-e DE-627 ger DE-627 rakwb eng Wen, Yicheng verfasserin aut A variance-estimation-based stopping rule for symbolic dynamic filtering 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2011 Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6. Probabilistic finite state automata (dpeaa)DE-He213 Markov chains (dpeaa)DE-He213 Variance estimation (dpeaa)DE-He213 Ray, Asok aut Du, Qiang aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 7(2011), 1 vom: 18. Feb., Seite 189-195 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:7 year:2011 number:1 day:18 month:02 pages:189-195 https://dx.doi.org/10.1007/s11760-011-0215-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2011 1 18 02 189-195
allfieldsSound	10.1007/s11760-011-0215-y doi (DE-627)SPR022266542 (SPR)s11760-011-0215-y-e DE-627 ger DE-627 rakwb eng Wen, Yicheng verfasserin aut A variance-estimation-based stopping rule for symbolic dynamic filtering 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Limited 2011 Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6. Probabilistic finite state automata (dpeaa)DE-He213 Markov chains (dpeaa)DE-He213 Variance estimation (dpeaa)DE-He213 Ray, Asok aut Du, Qiang aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 7(2011), 1 vom: 18. Feb., Seite 189-195 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:7 year:2011 number:1 day:18 month:02 pages:189-195 https://dx.doi.org/10.1007/s11760-011-0215-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2011 1 18 02 189-195
language	English
source	Enthalten in Signal, image and video processing 7(2011), 1 vom: 18. Feb., Seite 189-195 volume:7 year:2011 number:1 day:18 month:02 pages:189-195
sourceStr	Enthalten in Signal, image and video processing 7(2011), 1 vom: 18. Feb., Seite 189-195 volume:7 year:2011 number:1 day:18 month:02 pages:189-195
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Probabilistic finite state automata Markov chains Variance estimation
isfreeaccess_bool	false
container_title	Signal, image and video processing
authorswithroles_txt_mv	Wen, Yicheng @@aut@@ Ray, Asok @@aut@@ Du, Qiang @@aut@@
publishDateDaySort_date	2011-02-18T00:00:00Z
hierarchy_top_id	546899102
id	SPR022266542
language_de	englisch
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author	Wen, Yicheng
spellingShingle	Wen, Yicheng misc Probabilistic finite state automata misc Markov chains misc Variance estimation A variance-estimation-based stopping rule for symbolic dynamic filtering
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topic_title	A variance-estimation-based stopping rule for symbolic dynamic filtering Probabilistic finite state automata (dpeaa)DE-He213 Markov chains (dpeaa)DE-He213 Variance estimation (dpeaa)DE-He213
topic	misc Probabilistic finite state automata misc Markov chains misc Variance estimation
topic_unstemmed	misc Probabilistic finite state automata misc Markov chains misc Variance estimation
topic_browse	misc Probabilistic finite state automata misc Markov chains misc Variance estimation
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title	A variance-estimation-based stopping rule for symbolic dynamic filtering
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title_full	A variance-estimation-based stopping rule for symbolic dynamic filtering
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author_browse	Wen, Yicheng Ray, Asok Du, Qiang
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doi_str_mv	10.1007/s11760-011-0215-y
title_sort	variance-estimation-based stopping rule for symbolic dynamic filtering
title_auth	A variance-estimation-based stopping rule for symbolic dynamic filtering
abstract	Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6. © Springer-Verlag London Limited 2011
abstractGer	Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6. © Springer-Verlag London Limited 2011
abstract_unstemmed	Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. The algorithm of the proposed stopping rule is validated on ultrasonic data collected from a fatigue test apparatus for damage detection in the polycrystalline alloy 7075-T6. © Springer-Verlag London Limited 2011
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title_short	A variance-estimation-based stopping rule for symbolic dynamic filtering
url	https://dx.doi.org/10.1007/s11760-011-0215-y
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up_date	2024-07-04T02:29:09.749Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR022266542</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230330073516.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2011 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11760-011-0215-y</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR022266542</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11760-011-0215-y-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wen, Yicheng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A variance-estimation-based stopping rule for symbolic dynamic filtering</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2011</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag London Limited 2011</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract As an alternative to the batch means (BM) method in the stopping rule for symbolic dynamic filtering, this short paper presents an analytical procedure to estimate the variance parameter and to obtain a lower bound on the length of symbol blocks for constructing probabilistic finite state automata (PFSA). If the modulus of the second largest eigenvalue of the PFSA’s state transition matrix is relatively small or if the symbol block length is not too large, then the performance of the proposed stopping rule is superior to that of the stopping rule based on BM method. 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A variance-estimation-based stopping rule for symbolic dynamic filtering

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