Relative asynchronous index: a new measure for time series irreversibility
In this paper, we suggest a new measure for testing reversibility of time series which combines two different tools: the visibility algorithm and the inversion number. First, the visibility algorithm maps the time series to the network according to a geometric criterion. After that, the degree of ir...
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| Published in: | Nonlinear dynamics Vol. 93; no. 3; pp. 1545 - 1557 |
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| Language: | English |
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01.08.2018
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| Abstract | In this paper, we suggest a new measure for testing reversibility of time series which combines two different tools: the visibility algorithm and the inversion number. First, the visibility algorithm maps the time series to the network according to a geometric criterion. After that, the degree of irreversibility of the time series can be estimated by the relative asynchronous index (RAI), based on the inverse number, between out and
out
∗
degree sequences of the network (out and
out
∗
represent the outgoing sequence of forward time series and reverse time series, respectively). This method does not need to rely on additional parameters, so it can avoid the error caused by parameter estimation. In addition, we also study the multiscale RAI and find that the optimal scale selection for detection time irreversibility is 1–4. Different types of time series are used to confirm the validity of this metric. Finally, we apply the method to financial time series and find that the financial crisis can be detected by RAI. |
|---|---|
| AbstractList | In this paper, we suggest a new measure for testing reversibility of time series which combines two different tools: the visibility algorithm and the inversion number. First, the visibility algorithm maps the time series to the network according to a geometric criterion. After that, the degree of irreversibility of the time series can be estimated by the relative asynchronous index (RAI), based on the inverse number, between out and
out
∗
degree sequences of the network (out and
out
∗
represent the outgoing sequence of forward time series and reverse time series, respectively). This method does not need to rely on additional parameters, so it can avoid the error caused by parameter estimation. In addition, we also study the multiscale RAI and find that the optimal scale selection for detection time irreversibility is 1–4. Different types of time series are used to confirm the validity of this metric. Finally, we apply the method to financial time series and find that the financial crisis can be detected by RAI. In this paper, we suggest a new measure for testing reversibility of time series which combines two different tools: the visibility algorithm and the inversion number. First, the visibility algorithm maps the time series to the network according to a geometric criterion. After that, the degree of irreversibility of the time series can be estimated by the relative asynchronous index (RAI), based on the inverse number, between out and \[\hbox {out}^*\] degree sequences of the network (out and \[\hbox {out}^*\] represent the outgoing sequence of forward time series and reverse time series, respectively). This method does not need to rely on additional parameters, so it can avoid the error caused by parameter estimation. In addition, we also study the multiscale RAI and find that the optimal scale selection for detection time irreversibility is 1–4. Different types of time series are used to confirm the validity of this metric. Finally, we apply the method to financial time series and find that the financial crisis can be detected by RAI. In this paper, we suggest a new measure for testing reversibility of time series which combines two different tools: the visibility algorithm and the inversion number. First, the visibility algorithm maps the time series to the network according to a geometric criterion. After that, the degree of irreversibility of the time series can be estimated by the relative asynchronous index (RAI), based on the inverse number, between out and out∗ degree sequences of the network (out and out∗ represent the outgoing sequence of forward time series and reverse time series, respectively). This method does not need to rely on additional parameters, so it can avoid the error caused by parameter estimation. In addition, we also study the multiscale RAI and find that the optimal scale selection for detection time irreversibility is 1–4. Different types of time series are used to confirm the validity of this metric. Finally, we apply the method to financial time series and find that the financial crisis can be detected by RAI. |
| Author | Shang, Pengjian Yang, Pengbo |
| Author_xml | – sequence: 1 givenname: Pengbo surname: Yang fullname: Yang, Pengbo organization: Department of Mathematics, School of Science, Beijing Jiaotong University – sequence: 2 givenname: Pengjian surname: Shang fullname: Shang, Pengjian email: pjshang@bjtu.edu.cn organization: Department of Mathematics, School of Science, Beijing Jiaotong University |
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| Cites_doi | 10.1209/0295-5075/109/30005 10.1111/j.1467-9892.1982.tb00339.x 10.1016/j.physa.2003.08.022 10.1209/0295-5075/86/30001 10.1016/j.physrep.2006.11.001 10.1126/science.143.3613.1457 10.1103/PhysRevE.85.031129 10.1103/PhysRevE.77.066204 10.1103/PhysRevE.80.046103 10.1371/journal.pone.0142143 10.1016/j.amc.2016.05.013 10.1103/PhysRevE.62.1912 10.1016/0375-9601(96)00288-5 10.1140/epjb/e2012-20809-8 10.1093/oso/9780198522249.001.0001 10.1016/j.physleta.2016.03.011 10.1103/PhysRevLett.95.198102 10.1109/ICASSP.2007.366913 10.1007/s10955-004-3455-1 10.1073/pnas.0709247105 10.3390/e15031069 10.1093/biomet/86.2.483 10.1103/PhysRevLett.98.080602 10.1016/j.cnsns.2017.11.001 10.1098/rsta.2015.0182 10.1088/1367-2630/18/10/100201 10.1111/j.1467-9892.1991.tb00087.x 10.1103/PhysRevLett.98.150601 10.1088/1367-2630/11/7/073008 10.1109/ISBI.2004.1398484 10.1103/PhysRevLett.85.461 10.1007/s10558-007-9049-1 10.1063/1.166141 10.3390/e14060978 10.1142/S0218127417500596 10.1093/oso/9780198773191.001.0001 10.1103/PhysRevE.82.036120 10.1209/0295-5075/4/9/004 10.1016/j.chaos.2006.03.126 10.1103/PhysRevLett.90.108103 10.2307/3212735 10.1103/PhysRevLett.89.068102 10.1142/S0129065717500058 10.1103/PhysRevLett.105.150607 10.1109/TIT.2005.853314 10.1016/j.neuroimage.2013.08.056 10.1515/9780691218632 10.1016/0375-9601(95)00239-Y 10.1103/PhysRevE.69.056208 10.1142/S021812740100305X 10.1016/S0304-4076(99)00036-6 |
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| Keywords | Degree sequences Financial time series Visibility algorithm Inversion number Relative asynchronous index |
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| References | RoldánÉParrondoJMEstimating dissipation from single stationary trajectoriesPhys. Rev. Lett.201010515060710.1103/PhysRevLett.105.150607 TongHNon-linear Time Series: A Dynamical System Approach1990OxfordOxford University Press0716.62085 IvanovPCLiuKKBartschRPFocus on the emerging new fields of network physiology and network medicineNew J. Phys.20161810020110.1088/1367-2630/18/10/100201 GaoZKYangYXFangPCZouYXiaCYDuMMultiscale complex network for analyzing experimental multivariate time seriesEPL (Europhys. Lett.)20151093000510.1209/0295-5075/109/30005 CammarotaCRogoraETime reversal, symbolic series and irreversibility of human heartbeatChaos Solitons Fract.20073216491654229906010.1016/j.chaos.2006.03.1261195.92014 GaspardPTime-reversed dynamical entropy and irreversibility in Markovian random processesJ. Stat. Phys.2004117599615209972910.1007/s10955-004-3455-11113.82036 GaoZKZhangSSDangWDLiSCaiQMultilayer network from multivariate time series for characterizing nonlinear flow behaviorInt. J. Bifurc. Chaos201727175005910.1142/S0218127417500596 LacasaLLuqueBLuqueJNunoJCThe visibility graph: a new method for estimating the Hurst exponent of fractional Brownian motionEPL (Europhys. Lett.)2009863000110.1209/0295-5075/86/30001 WuSDWuCWLinSGWangCCLeeKYTime series analysis using composite multiscale entropyEntropy20131510691084304114510.3390/e150310691298.65020 HamiltonJDTime Series Analysis1994PrincetonPrinceton University Press0831.62061 FlanaganRLacasaLIrreversibility of financial time series: a graph-theoretical approachPhys. Lett. A20163801689169710.1016/j.physleta.2016.03.011 CasaliKRCasaliAGMontanoNIrigoyenMCMacagnanFGuzzettiSPortaAMultiple testing strategy for the detection of temporal irreversibility in stationary time seriesPhys. Rev. E20087706620410.1103/PhysRevE.77.066204 ParrondoJMVan den BroeckCKawaiREntropy production and the arrow of timeNew J. Phys.20091107300810.1088/1367-2630/11/7/073008 YangPShangPRecurrence quantity analysis based on matrix eigenvaluesCommun. Nonlinear Sci. Numer. Simul.2018591529375837010.1016/j.cnsns.2017.11.001 SharifdoustMMahmoodiSOn time reversibility of linear time seriesJ. Math. Ext.20136334732477171332.62303 CoxDRLong-range dependence, non-linearity and time irreversibilityJ. Time Ser. Anal.199112329335113100510.1111/j.1467-9892.1991.tb00087.x0735.62088 GaoZKCaiQYangYXDongNZhangSSVisibility graph from adaptive optimal kernel time-frequency representation for classification of epileptiform EEGInt. J. Neural Syst.201727175000510.1142/S0129065717500058 Van der HeydenMDiksCPijnJVelisDTime reversibility of intracranial human EEG recordings in mesial temporal lobe epilepsyPhys. Lett. A199621628328810.1016/0375-9601(96)00288-5 LacasaLLuqueBBallesterosFLuqueJNunoJCFrom time series to complex networks: the visibility graphProc. Natl. Acad. Sci.200810549724975240309610.1073/pnas.07092471051205.05162 EckmannJPKamphorstSORuelleDRecurrence plots of dynamical systemsEPL (Europhys. Lett.)1987497310.1209/0295-5075/4/9/004 Hershey, J.R., Olsen, P.A.: Approximating the Kullback–Leibler divergence between Gaussian mixture models. In: Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on, vol. 4, pp. IV–317. IEEE (2007) MarwanNRomanoMCThielMKurthsJRecurrence plots for the analysis of complex systemsPhys. Rep.2007438237329229169910.1016/j.physrep.2006.11.001 SprottJCRowlandsGImproved correlation dimension calculationInt. J. Bifurc. Chaos20011118651880185691210.1142/S021812740100305X1090.37561 YangACCHseuSSYienHWGoldbergerALPengCKLinguistic analysis of the human heartbeat using frequency and rank order statisticsPhys. Rev. Lett.20039010810310.1103/PhysRevLett.90.108103 CostaMGoldbergerALPengCKBroken asymmetry of the human heartbeat: loss of time irreversibility in aging and diseasePhys. Rev. Lett.20059519810210.1103/PhysRevLett.95.198102 ChenYTChouRYKuanCMTesting time reversibility without moment restrictionsJ. Econom.20009519921810.1016/S0304-4076(99)00036-60970.62053 WangQKulkarniSRVerdúSDivergence estimation of continuous distributions based on data-dependent partitionsIEEE Trans. Inf. Theory20055130643074223913610.1109/TIT.2005.8533141310.94055 LiuQWeiQFanSZLuCWLinTYAbbodMFShiehJSAdaptive computation of multiscale entropy and its application in EEG signals for monitoring depth of anesthesia during surgeryEntropy20121497899210.3390/e140609781303.92045 SchreiberTMeasuring information transferPhys. Rev. Lett.20008546110.1103/PhysRevLett.85.461 AndrieuxDGaspardPCilibertoSGarnierNJoubaudSPetrosyanAEntropy production and time asymmetry in nonequilibrium fluctuationsPhys. Rev. Lett.20079815060110.1103/PhysRevLett.98.150601 Priestley, M.B.: Spectral analysis and time series. J. Am. Stat. Assoc. 79, 385 (1981) LinALiuKKBartschRPIvanovPCDelay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactionsPhilos. Trans. R. Soc. A20163742015018210.1098/rsta.2015.0182 KennelMBTesting time symmetry in time series using data compression dictionariesPhys. Rev. E20046905620810.1103/PhysRevE.69.056208 LacasaLToralRDescription of stochastic and chaotic series using visibility graphsPhys. Rev. E20108203612010.1103/PhysRevE.82.036120 ThomasJACoverTMElements of information theory2006HobokenWiley1140.94001 BroderGWeilMHExcess lactate: an index of reversibility of shock in human patientsScience19641431457145910.1126/science.143.3613.1457 ChengQOn time-reversibility of linear processesBiometrika199986483486170536610.1093/biomet/86.2.4830933.60034 KawaiRParrondoJVan den BroeckCDissipation: the phase-space perspectivePhys. Rev. Lett.20079808060210.1103/PhysRevLett.98.080602 CostaMGoldbergerALPengCKMultiscale entropy analysis of complex physiologic time seriesPhys. Rev. Lett.20028906810210.1103/PhysRevLett.89.068102 LacasaLNunezARoldánÉParrondoJMLuqueBTime series irreversibility: a visibility graph approachEur. Phys. J. B20128511110.1140/epjb/e2012-20809-8 Weisenfeld, N.L., Warfteld, S.: Normalization of joint image-intensity statistics in MRI using the Kullback-Leibler divergence. In: Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on, pp. 101–104. IEEE (2004) CostaMPengCKGoldbergerALHausdorffJMMultiscale entropy analysis of human gait dynamicsPhysica A2003330536010.1016/j.physa.2003.08.0221029.92003 LobierMSiebenhühnerFPalvaSPalvaJMPhase transfer entropy: a novel phase-based measure for directed connectivity in networks coupled by oscillatory interactionsNeuroimage20148585387210.1016/j.neuroimage.2013.08.056 HinichMJTesting for Gaussianity and linearity of a stationary time seriesJ. Time Ser. Anal.1982316917669522810.1111/j.1467-9892.1982.tb00339.x0502.62079 Granger, C.W., Terasvirta, T., et al.: Modelling non-linear economic relationships. OUP Catalogue (1993) LuqueBLacasaLBallesterosFLuqueJHorizontal visibility graphs: exact results for random time seriesPhys. Rev. E20098004610310.1103/PhysRevE.80.046103 RoldánÉParrondoJMEntropy production and Kullback–Leibler divergence between stationary trajectories of discrete systemsPhys. Rev. E20128503112910.1103/PhysRevE.85.031129 WeissGTime-reversibility of linear stochastic processesJ. Appl. Probab.19751283183638599810.2307/32127350322.60037 DiksCVan HouwelingenJTakensFDeGoedeJReversibility as a criterion for discriminating time seriesPhys. Lett. A199520122122810.1016/0375-9601(95)00239-Y CostaMDPengCKGoldbergerALMultiscale analysis of heart rate dynamics: entropy and time irreversibility measuresCardiovasc. Eng.20088889310.1007/s10558-007-9049-1 PengCKHavlinSStanleyHEGoldbergerALQuantification of scaling exponents and crossover phenomena in nonstationary heartbeat time seriesChaos19955828710.1063/1.166141 DawCFinneyCKennelMSymbolic approach for measuring temporal irreversibilityPhys. Rev. E200062191210.1103/PhysRevE.62.1912 YinYShangPFengGModified multiscale cross-sample entropy for complex time seriesAppl. Math. Comput.2016289981103515840 BartschRPLiuKKBashanAIvanovPCNetwork physiology: how organ systems dynamically interactPLoS ONE201510e014214310.1371/journal.pone.0142143 DickeyDAFullerWADistribution of the estimators for autoregressive time series with a unit rootJ. Am. Stat. Assoc.1979744274315480360413.62075 YT Chen (4275_CR26) 2000; 95 JP Eckmann (4275_CR5) 1987; 4 RP Bartsch (4275_CR55) 2015; 10 JA Thomas (4275_CR38) 2006 P Yang (4275_CR12) 2018; 59 ZK Gao (4275_CR48) 2017; 27 C Cammarota (4275_CR18) 2007; 32 KR Casali (4275_CR43) 2008; 77 SD Wu (4275_CR52) 2013; 15 H Tong (4275_CR27) 1990 L Lacasa (4275_CR42) 2010; 82 M Costa (4275_CR7) 2002; 89 4275_CR47 4275_CR46 JC Sprott (4275_CR53) 2001; 11 MJ Hinich (4275_CR22) 1982; 3 C Daw (4275_CR33) 2000; 62 ACC Yang (4275_CR15) 2003; 90 C Diks (4275_CR13) 1995; 201 É Roldán (4275_CR31) 2012; 85 M Heyden Van der (4275_CR14) 1996; 216 L Lacasa (4275_CR44) 2012; 85 DA Dickey (4275_CR2) 1979; 74 M Sharifdoust (4275_CR23) 2013; 6 Q Wang (4275_CR37) 2005; 51 A Lin (4275_CR32) 2016; 374 MB Kennel (4275_CR34) 2004; 69 Y Yin (4275_CR51) 2016; 289 R Kawai (4275_CR24) 2007; 98 T Schreiber (4275_CR6) 2000; 85 L Lacasa (4275_CR41) 2009; 86 JD Hamilton (4275_CR1) 1994 P Gaspard (4275_CR35) 2004; 117 M Lobier (4275_CR11) 2014; 85 CK Peng (4275_CR8) 1995; 5 D Andrieux (4275_CR36) 2007; 98 ZK Gao (4275_CR9) 2015; 109 G Broder (4275_CR19) 1964; 143 L Lacasa (4275_CR40) 2008; 105 M Costa (4275_CR16) 2005; 95 4275_CR28 B Luque (4275_CR39) 2009; 80 DR Cox (4275_CR29) 1991; 12 G Weiss (4275_CR20) 1975; 12 JM Parrondo (4275_CR25) 2009; 11 4275_CR3 R Flanagan (4275_CR45) 2016; 380 Q Cheng (4275_CR21) 1999; 86 Q Liu (4275_CR50) 2012; 14 PC Ivanov (4275_CR54) 2016; 18 ZK Gao (4275_CR10) 2017; 27 É Roldán (4275_CR30) 2010; 105 N Marwan (4275_CR4) 2007; 438 M Costa (4275_CR49) 2003; 330 MD Costa (4275_CR17) 2008; 8 |
| References_xml | – reference: CostaMGoldbergerALPengCKMultiscale entropy analysis of complex physiologic time seriesPhys. Rev. Lett.20028906810210.1103/PhysRevLett.89.068102 – reference: HinichMJTesting for Gaussianity and linearity of a stationary time seriesJ. Time Ser. Anal.1982316917669522810.1111/j.1467-9892.1982.tb00339.x0502.62079 – reference: ThomasJACoverTMElements of information theory2006HobokenWiley1140.94001 – reference: IvanovPCLiuKKBartschRPFocus on the emerging new fields of network physiology and network medicineNew J. Phys.20161810020110.1088/1367-2630/18/10/100201 – reference: LobierMSiebenhühnerFPalvaSPalvaJMPhase transfer entropy: a novel phase-based measure for directed connectivity in networks coupled by oscillatory interactionsNeuroimage20148585387210.1016/j.neuroimage.2013.08.056 – reference: KawaiRParrondoJVan den BroeckCDissipation: the phase-space perspectivePhys. Rev. Lett.20079808060210.1103/PhysRevLett.98.080602 – reference: FlanaganRLacasaLIrreversibility of financial time series: a graph-theoretical approachPhys. Lett. A20163801689169710.1016/j.physleta.2016.03.011 – reference: CostaMPengCKGoldbergerALHausdorffJMMultiscale entropy analysis of human gait dynamicsPhysica A2003330536010.1016/j.physa.2003.08.0221029.92003 – reference: WangQKulkarniSRVerdúSDivergence estimation of continuous distributions based on data-dependent partitionsIEEE Trans. Inf. Theory20055130643074223913610.1109/TIT.2005.8533141310.94055 – reference: HamiltonJDTime Series Analysis1994PrincetonPrinceton University Press0831.62061 – reference: KennelMBTesting time symmetry in time series using data compression dictionariesPhys. Rev. E20046905620810.1103/PhysRevE.69.056208 – reference: Priestley, M.B.: Spectral analysis and time series. J. Am. Stat. Assoc. 79, 385 (1981) – reference: BroderGWeilMHExcess lactate: an index of reversibility of shock in human patientsScience19641431457145910.1126/science.143.3613.1457 – reference: CostaMGoldbergerALPengCKBroken asymmetry of the human heartbeat: loss of time irreversibility in aging and diseasePhys. Rev. Lett.20059519810210.1103/PhysRevLett.95.198102 – reference: LacasaLToralRDescription of stochastic and chaotic series using visibility graphsPhys. Rev. E20108203612010.1103/PhysRevE.82.036120 – reference: SharifdoustMMahmoodiSOn time reversibility of linear time seriesJ. Math. Ext.20136334732477171332.62303 – reference: TongHNon-linear Time Series: A Dynamical System Approach1990OxfordOxford University Press0716.62085 – reference: WuSDWuCWLinSGWangCCLeeKYTime series analysis using composite multiscale entropyEntropy20131510691084304114510.3390/e150310691298.65020 – reference: GaoZKYangYXFangPCZouYXiaCYDuMMultiscale complex network for analyzing experimental multivariate time seriesEPL (Europhys. Lett.)20151093000510.1209/0295-5075/109/30005 – reference: Weisenfeld, N.L., Warfteld, S.: Normalization of joint image-intensity statistics in MRI using the Kullback-Leibler divergence. In: Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on, pp. 101–104. IEEE (2004) – reference: Granger, C.W., Terasvirta, T., et al.: Modelling non-linear economic relationships. OUP Catalogue (1993) – reference: LinALiuKKBartschRPIvanovPCDelay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactionsPhilos. Trans. R. Soc. A20163742015018210.1098/rsta.2015.0182 – reference: LacasaLLuqueBBallesterosFLuqueJNunoJCFrom time series to complex networks: the visibility graphProc. Natl. Acad. Sci.200810549724975240309610.1073/pnas.07092471051205.05162 – reference: LacasaLNunezARoldánÉParrondoJMLuqueBTime series irreversibility: a visibility graph approachEur. Phys. J. B20128511110.1140/epjb/e2012-20809-8 – reference: GaoZKZhangSSDangWDLiSCaiQMultilayer network from multivariate time series for characterizing nonlinear flow behaviorInt. J. Bifurc. Chaos201727175005910.1142/S0218127417500596 – reference: CostaMDPengCKGoldbergerALMultiscale analysis of heart rate dynamics: entropy and time irreversibility measuresCardiovasc. Eng.20088889310.1007/s10558-007-9049-1 – reference: AndrieuxDGaspardPCilibertoSGarnierNJoubaudSPetrosyanAEntropy production and time asymmetry in nonequilibrium fluctuationsPhys. Rev. Lett.20079815060110.1103/PhysRevLett.98.150601 – reference: DickeyDAFullerWADistribution of the estimators for autoregressive time series with a unit rootJ. Am. Stat. Assoc.1979744274315480360413.62075 – reference: PengCKHavlinSStanleyHEGoldbergerALQuantification of scaling exponents and crossover phenomena in nonstationary heartbeat time seriesChaos19955828710.1063/1.166141 – reference: DiksCVan HouwelingenJTakensFDeGoedeJReversibility as a criterion for discriminating time seriesPhys. Lett. A199520122122810.1016/0375-9601(95)00239-Y – reference: EckmannJPKamphorstSORuelleDRecurrence plots of dynamical systemsEPL (Europhys. Lett.)1987497310.1209/0295-5075/4/9/004 – reference: ChenYTChouRYKuanCMTesting time reversibility without moment restrictionsJ. Econom.20009519921810.1016/S0304-4076(99)00036-60970.62053 – reference: GaspardPTime-reversed dynamical entropy and irreversibility in Markovian random processesJ. Stat. Phys.2004117599615209972910.1007/s10955-004-3455-11113.82036 – reference: LiuQWeiQFanSZLuCWLinTYAbbodMFShiehJSAdaptive computation of multiscale entropy and its application in EEG signals for monitoring depth of anesthesia during surgeryEntropy20121497899210.3390/e140609781303.92045 – reference: WeissGTime-reversibility of linear stochastic processesJ. Appl. Probab.19751283183638599810.2307/32127350322.60037 – reference: CoxDRLong-range dependence, non-linearity and time irreversibilityJ. Time Ser. Anal.199112329335113100510.1111/j.1467-9892.1991.tb00087.x0735.62088 – reference: YangPShangPRecurrence quantity analysis based on matrix eigenvaluesCommun. Nonlinear Sci. Numer. Simul.2018591529375837010.1016/j.cnsns.2017.11.001 – reference: SchreiberTMeasuring information transferPhys. Rev. Lett.20008546110.1103/PhysRevLett.85.461 – reference: LacasaLLuqueBLuqueJNunoJCThe visibility graph: a new method for estimating the Hurst exponent of fractional Brownian motionEPL (Europhys. Lett.)2009863000110.1209/0295-5075/86/30001 – reference: ChengQOn time-reversibility of linear processesBiometrika199986483486170536610.1093/biomet/86.2.4830933.60034 – reference: SprottJCRowlandsGImproved correlation dimension calculationInt. J. Bifurc. Chaos20011118651880185691210.1142/S021812740100305X1090.37561 – reference: RoldánÉParrondoJMEntropy production and Kullback–Leibler divergence between stationary trajectories of discrete systemsPhys. Rev. E20128503112910.1103/PhysRevE.85.031129 – reference: CasaliKRCasaliAGMontanoNIrigoyenMCMacagnanFGuzzettiSPortaAMultiple testing strategy for the detection of temporal irreversibility in stationary time seriesPhys. Rev. E20087706620410.1103/PhysRevE.77.066204 – reference: Van der HeydenMDiksCPijnJVelisDTime reversibility of intracranial human EEG recordings in mesial temporal lobe epilepsyPhys. Lett. A199621628328810.1016/0375-9601(96)00288-5 – reference: LuqueBLacasaLBallesterosFLuqueJHorizontal visibility graphs: exact results for random time seriesPhys. Rev. E20098004610310.1103/PhysRevE.80.046103 – reference: DawCFinneyCKennelMSymbolic approach for measuring temporal irreversibilityPhys. Rev. E200062191210.1103/PhysRevE.62.1912 – reference: YinYShangPFengGModified multiscale cross-sample entropy for complex time seriesAppl. Math. Comput.2016289981103515840 – reference: Hershey, J.R., Olsen, P.A.: Approximating the Kullback–Leibler divergence between Gaussian mixture models. In: Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on, vol. 4, pp. IV–317. IEEE (2007) – reference: BartschRPLiuKKBashanAIvanovPCNetwork physiology: how organ systems dynamically interactPLoS ONE201510e014214310.1371/journal.pone.0142143 – reference: RoldánÉParrondoJMEstimating dissipation from single stationary trajectoriesPhys. Rev. Lett.201010515060710.1103/PhysRevLett.105.150607 – reference: GaoZKCaiQYangYXDongNZhangSSVisibility graph from adaptive optimal kernel time-frequency representation for classification of epileptiform EEGInt. J. Neural Syst.201727175000510.1142/S0129065717500058 – reference: CammarotaCRogoraETime reversal, symbolic series and irreversibility of human heartbeatChaos Solitons Fract.20073216491654229906010.1016/j.chaos.2006.03.1261195.92014 – reference: YangACCHseuSSYienHWGoldbergerALPengCKLinguistic analysis of the human heartbeat using frequency and rank order statisticsPhys. Rev. Lett.20039010810310.1103/PhysRevLett.90.108103 – reference: MarwanNRomanoMCThielMKurthsJRecurrence plots for the analysis of complex systemsPhys. Rep.2007438237329229169910.1016/j.physrep.2006.11.001 – reference: ParrondoJMVan den BroeckCKawaiREntropy production and the arrow of timeNew J. Phys.20091107300810.1088/1367-2630/11/7/073008 – volume: 109 start-page: 30005 year: 2015 ident: 4275_CR9 publication-title: EPL (Europhys. Lett.) doi: 10.1209/0295-5075/109/30005 – volume: 6 start-page: 33 year: 2013 ident: 4275_CR23 publication-title: J. Math. Ext. – volume: 3 start-page: 169 year: 1982 ident: 4275_CR22 publication-title: J. Time Ser. Anal. doi: 10.1111/j.1467-9892.1982.tb00339.x – ident: 4275_CR3 – volume: 330 start-page: 53 year: 2003 ident: 4275_CR49 publication-title: Physica A doi: 10.1016/j.physa.2003.08.022 – volume: 86 start-page: 30001 year: 2009 ident: 4275_CR41 publication-title: EPL (Europhys. Lett.) doi: 10.1209/0295-5075/86/30001 – volume: 438 start-page: 237 year: 2007 ident: 4275_CR4 publication-title: Phys. Rep. doi: 10.1016/j.physrep.2006.11.001 – volume: 143 start-page: 1457 year: 1964 ident: 4275_CR19 publication-title: Science doi: 10.1126/science.143.3613.1457 – volume: 74 start-page: 427 year: 1979 ident: 4275_CR2 publication-title: J. Am. Stat. Assoc. – volume: 85 start-page: 031129 year: 2012 ident: 4275_CR31 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.85.031129 – volume: 77 start-page: 066204 year: 2008 ident: 4275_CR43 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.77.066204 – volume: 80 start-page: 046103 year: 2009 ident: 4275_CR39 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.80.046103 – volume: 10 start-page: e0142143 year: 2015 ident: 4275_CR55 publication-title: PLoS ONE doi: 10.1371/journal.pone.0142143 – volume: 289 start-page: 98 year: 2016 ident: 4275_CR51 publication-title: Appl. Math. Comput. doi: 10.1016/j.amc.2016.05.013 – volume: 62 start-page: 1912 year: 2000 ident: 4275_CR33 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.62.1912 – volume: 216 start-page: 283 year: 1996 ident: 4275_CR14 publication-title: Phys. Lett. A doi: 10.1016/0375-9601(96)00288-5 – volume: 85 start-page: 1 year: 2012 ident: 4275_CR44 publication-title: Eur. Phys. J. B doi: 10.1140/epjb/e2012-20809-8 – volume-title: Non-linear Time Series: A Dynamical System Approach year: 1990 ident: 4275_CR27 doi: 10.1093/oso/9780198522249.001.0001 – volume: 380 start-page: 1689 year: 2016 ident: 4275_CR45 publication-title: Phys. Lett. A doi: 10.1016/j.physleta.2016.03.011 – volume: 95 start-page: 198102 year: 2005 ident: 4275_CR16 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.95.198102 – ident: 4275_CR47 doi: 10.1109/ICASSP.2007.366913 – volume: 117 start-page: 599 year: 2004 ident: 4275_CR35 publication-title: J. Stat. Phys. doi: 10.1007/s10955-004-3455-1 – volume: 105 start-page: 4972 year: 2008 ident: 4275_CR40 publication-title: Proc. Natl. Acad. Sci. doi: 10.1073/pnas.0709247105 – volume: 15 start-page: 1069 year: 2013 ident: 4275_CR52 publication-title: Entropy doi: 10.3390/e15031069 – volume: 86 start-page: 483 year: 1999 ident: 4275_CR21 publication-title: Biometrika doi: 10.1093/biomet/86.2.483 – volume: 98 start-page: 080602 year: 2007 ident: 4275_CR24 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.98.080602 – volume: 59 start-page: 15 year: 2018 ident: 4275_CR12 publication-title: Commun. Nonlinear Sci. Numer. Simul. doi: 10.1016/j.cnsns.2017.11.001 – volume: 374 start-page: 20150182 year: 2016 ident: 4275_CR32 publication-title: Philos. Trans. R. Soc. A doi: 10.1098/rsta.2015.0182 – volume: 18 start-page: 100201 year: 2016 ident: 4275_CR54 publication-title: New J. Phys. doi: 10.1088/1367-2630/18/10/100201 – volume: 12 start-page: 329 year: 1991 ident: 4275_CR29 publication-title: J. Time Ser. Anal. doi: 10.1111/j.1467-9892.1991.tb00087.x – volume: 98 start-page: 150601 year: 2007 ident: 4275_CR36 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.98.150601 – volume: 11 start-page: 073008 year: 2009 ident: 4275_CR25 publication-title: New J. Phys. doi: 10.1088/1367-2630/11/7/073008 – ident: 4275_CR46 doi: 10.1109/ISBI.2004.1398484 – volume: 85 start-page: 461 year: 2000 ident: 4275_CR6 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.85.461 – volume: 8 start-page: 88 year: 2008 ident: 4275_CR17 publication-title: Cardiovasc. Eng. doi: 10.1007/s10558-007-9049-1 – volume: 5 start-page: 82 year: 1995 ident: 4275_CR8 publication-title: Chaos doi: 10.1063/1.166141 – volume: 14 start-page: 978 year: 2012 ident: 4275_CR50 publication-title: Entropy doi: 10.3390/e14060978 – volume: 27 start-page: 1750059 year: 2017 ident: 4275_CR10 publication-title: Int. J. Bifurc. Chaos doi: 10.1142/S0218127417500596 – ident: 4275_CR28 doi: 10.1093/oso/9780198773191.001.0001 – volume: 82 start-page: 036120 year: 2010 ident: 4275_CR42 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.82.036120 – volume: 4 start-page: 973 year: 1987 ident: 4275_CR5 publication-title: EPL (Europhys. Lett.) doi: 10.1209/0295-5075/4/9/004 – volume: 32 start-page: 1649 year: 2007 ident: 4275_CR18 publication-title: Chaos Solitons Fract. doi: 10.1016/j.chaos.2006.03.126 – volume: 90 start-page: 108103 year: 2003 ident: 4275_CR15 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.90.108103 – volume-title: Elements of information theory year: 2006 ident: 4275_CR38 – volume: 12 start-page: 831 year: 1975 ident: 4275_CR20 publication-title: J. Appl. Probab. doi: 10.2307/3212735 – volume: 89 start-page: 068102 year: 2002 ident: 4275_CR7 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.89.068102 – volume: 27 start-page: 1750005 year: 2017 ident: 4275_CR48 publication-title: Int. J. Neural Syst. doi: 10.1142/S0129065717500058 – volume: 105 start-page: 150607 year: 2010 ident: 4275_CR30 publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.105.150607 – volume: 51 start-page: 3064 year: 2005 ident: 4275_CR37 publication-title: IEEE Trans. Inf. Theory doi: 10.1109/TIT.2005.853314 – volume: 85 start-page: 853 year: 2014 ident: 4275_CR11 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.08.056 – volume-title: Time Series Analysis year: 1994 ident: 4275_CR1 doi: 10.1515/9780691218632 – volume: 201 start-page: 221 year: 1995 ident: 4275_CR13 publication-title: Phys. Lett. A doi: 10.1016/0375-9601(95)00239-Y – volume: 69 start-page: 056208 year: 2004 ident: 4275_CR34 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.69.056208 – volume: 11 start-page: 1865 year: 2001 ident: 4275_CR53 publication-title: Int. J. Bifurc. Chaos doi: 10.1142/S021812740100305X – volume: 95 start-page: 199 year: 2000 ident: 4275_CR26 publication-title: J. Econom. doi: 10.1016/S0304-4076(99)00036-6 |
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| SubjectTerms | Algorithms Automotive Engineering Classical Mechanics Control Dynamical Systems Engineering Mechanical Engineering Multiscale analysis Original Paper Parameter estimation Regression analysis Sequences Time series Vibration Visibility |
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| Title | Relative asynchronous index: a new measure for time series irreversibility |
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