Academic literature on the topic 'Multifractal time series'
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Journal articles on the topic "Multifractal time series"
Holdsworth, Amber M., Nicholas K. R. Kevlahan, and David J. D. Earn. "Multifractal signatures of infectious diseases." Journal of The Royal Society Interface 9, no. 74 (March 22, 2012): 2167–80. http://dx.doi.org/10.1098/rsif.2011.0886.
Full textBakucz, Peter, and Gabor Kiss. "Modeling of probable maximum values in autonomous driving." SYSTEM THEORY, CONTROL AND COMPUTING JOURNAL 1, no. 2 (December 31, 2021): 58–64. http://dx.doi.org/10.52846/stccj.2021.1.2.28.
Full textKLEMENT, STEPHAN, KARL W. KRATKY, and JOHANN NITTMANN. "PRACTICAL TIME-SERIES ANALYSIS WITH MULTIFRACTAL METHODS." Fractals 01, no. 03 (September 1993): 735–43. http://dx.doi.org/10.1142/s0218348x93000770.
Full textFigueirêdo, P. H., E. Nogueira, M. A. Moret, and Sérgio Coutinho. "Multifractal analysis of polyalanines time series." Physica A: Statistical Mechanics and its Applications 389, no. 10 (May 2010): 2090–95. http://dx.doi.org/10.1016/j.physa.2009.11.045.
Full textLi, Yun Fa. "Application of Multifractal Statistics Method on Time Series." Applied Mechanics and Materials 556-562 (May 2014): 4559–62. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4559.
Full textTzanis, Chris G., Ioannis Koutsogiannis, Kostas Philippopoulos, and Nikolaos Kalamaras. "Multifractal Detrended Cross-Correlation Analysis of Global Methane and Temperature." Remote Sensing 12, no. 3 (February 7, 2020): 557. http://dx.doi.org/10.3390/rs12030557.
Full textKalisky, Tomer, Yosef Ashkenazy, and Shlomo Havlin. "Volatility of fractal and multifractal time series." Israel Journal of Earth Sciences 56, no. 1 (December 1, 2007): 47–56. http://dx.doi.org/10.1560/ijes.56.1.47.
Full textWang, Jeen-Hwa, and Chung-Wein Lee. "Multifractal Measures of Time Series of Earthquakes." Journal of Physics of the Earth 45, no. 5 (1997): 331–45. http://dx.doi.org/10.4294/jpe1952.45.331.
Full textTuriel, Antonio, and Conrad J. Pérez-Vicente. "Multifractal geometry in stock market time series." Physica A: Statistical Mechanics and its Applications 322 (May 2003): 629–49. http://dx.doi.org/10.1016/s0378-4371(02)01830-7.
Full textXiong, Hui, and Pengjian Shang. "Weighted multifractal analysis of financial time series." Nonlinear Dynamics 87, no. 4 (November 10, 2016): 2251–66. http://dx.doi.org/10.1007/s11071-016-3187-1.
Full textDissertations / Theses on the topic "Multifractal time series"
Булах, В. А., Л. О. Кіріченко, and Т. А. Радівілова. "Classification of Multifractal Time Series by Decision Tree Methods." Thesis, КНУ, 2018. http://openarchive.nure.ua/handle/document/5840.
Full textSnguanyat, Ongorn. "Stochastic modelling of financial time series with memory and multifractal scaling." Queensland University of Technology, 2009. http://eprints.qut.edu.au/30240/.
Full textZhou, Xiaobo. "Fractal and Multifractal Analysis of Runoff Time Series and Stream Networks in Agricultural Watersheds." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/11287.
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Nascimento, César Moura. "Análise multifractal e seções de Lévy de flutuações heterocedásticas." Universidade Federal de Alagoas, 2008. http://repositorio.ufal.br/handle/riufal/1012.
Full textConselho Nacional de Desenvolvimento Científico e Tecnológico
Um importante problema em Física está relacionado ao estudo de processos estocásticos e flutuações de variáveis dinâmicas. Em uma variedade de sistemas, algumas das variáveis observadas têm uma qualidade macroscópica, no sentido de que elas representam a média ou a soma sobre o espaço ou tempo de quantidades microscópicas. Quando efeitos de memória de longo alcance ou correlação não desempenharem um papel significativo, então as condições necessárias e suficientes para a validade do Teorema do Limite Central podem ser satisfeitas. Frequentemente o segundo momento da variável em questão não diverge. Consequentemente em muitos exemplos importantes, as flutuações de muitos sistemas seguem uma estatística Gaussiana. Em contraste, sistemas complexos geram flutuações que muitas vezes os desviam da estatística Gaussiana. Aqui, nós focamos em duas propriedades relacionadas à flutuações Gaussianas: (i) monofractalidade e (ii) homocedasticidade. Especificamente, discutimos primeiro a questão geral sobre a natureza da relação entre multifractalidade e heterocedasticidade. Aplicamos a multifractal detrended fluctuations analysis a uma série temporal financeira não estacionária e de alta freqüência referente à taxa cambial. Como um segundo teste, aplicamos a mesma técnica de análise para a série de áudio da quinta sinfonia de Beethoven. Obtivemos resultados que indicam que a heterocedasticidade pode causar ou aumentar a multifractalidade. Também investigamos em detalhes a convergência para o regime homocedástico e monofratal Gaussiano usando o método matemático de seções de Lévy, como previamente aplicado a séries temporais. Apresentamos conclusões relacionadas a estes questionamentos e discutimos a generalidade destes resultados no contexto da Física de sistemas complexos.
Олемской, Александр Иванович, Олександр Іванович Олємской, Oleksandr Ivanovych Oliemskoi, and Э. Ф. Галимарданова. "Мультифрактальный анализ временных рядов." Thesis, Изд-во СумГУ, 2008. http://essuir.sumdu.edu.ua/handle/123456789/3954.
Full textОлемской, Александр Иванович, Олександр Іванович Олємской, Oleksandr Ivanovych Oliemskoi, Вадим Николаевич Борисюк, Вадим Миколайович Борисюк, and Vadym Mykolaiovych Borysiuk. "Мультифрактальный анализ самоподобных временных рядов." Thesis, Изд-во СумГУ, 2009. http://essuir.sumdu.edu.ua/handle/123456789/3886.
Full textHoang, Cong Tuan. "Prise en compte des fluctuations spatio-temporelles pluies-débits pour une meilleure gestion de la ressource en eau et une meilleure évaluation des risques." Phd thesis, Université Paris-Est, 2011. http://pastel.archives-ouvertes.fr/pastel-00658537.
Full textFonseca, Eder Lucio da. "O estudo das propriedades multifractais de séries temporais financeiras." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/100/100132/tde-07052012-230908/.
Full textFinancial time series such as market index and asset prices, are produced by complex interactions of agents that trade in the market. The fractal and multifractal properties of these series provides evidence for early detection of the occurrence of sudden market movements (crashes). This evidence is obtained by applying the concept of Analog Specific Heat C(q), from the equivalence between the Multifractal Analysis and Thermodynamics. In the vicinity of a crash, C(q) exhibits a shoulder at the right side of its curve, while in the absence of a crash, C(q) presents a form similar to a Gaussian distribution curve. Based on this behavior, it is proposed in this work a new temporal indicator IA(i) defined here as the area variation rate over the Specific Heat function. We have constructed the mentioned indicator from a window of data with the first points (size s), that moves throughout the series, simulating the actual input of data over time. The indicator IA(i) allows one detecting in advance the occurrence of large financial market movements, such as those occurred in 1929 and 1987 for the marked indexes Dow Jones, Nasdaq and S&P500. Moreover, the simultaneous analysis of measures such as the Free Energy, Multifractal Dimension and Multifractal Spectrum suggest that a market crash resembles a phase transition. The robustness of the method for others assets and different periods of time demonstrates the importance of the results. Moreover, nonlinear statistical models for volatility have been employed in the work to study large fluctuations caused by crashes and financial crises over time.
Huang, Yongxiang. "ARBITRARY ORDER HILBERT SPECTRAL ANALYSIS DEFINITION AND APPLICATION TO FULLY DEVELOPED TURBULENCE AND ENVIRONMENTAL TIME SERIES." Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2009. http://tel.archives-ouvertes.fr/tel-00439605.
Full textБулах, В. А., Л. О. Кіріченко, and Т. А. Радівілова. "Time Series Classification Based on Fractal Properties." Thesis, 2018. http://openarchive.nure.ua/handle/document/9452.
Full textBooks on the topic "Multifractal time series"
Sattarhoff, Cristina. Statistical Inference in Multifractal Random Walk Models for Financial Time Series. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2011.
Find full textSattarhoff, Cristina. Statistical Inference in Multifractal Random Walk Models for Financial Time Series. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2012.
Find full textLux, Thomas, and Mawuli Segnon. Multifractal Models in Finance. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.8.
Full textBook chapters on the topic "Multifractal time series"
Kantelhardt, Jan W. "Fractal and Multifractal Time Series." In Mathematics of Complexity and Dynamical Systems, 463–87. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-1806-1_30.
Full textKantelhardt, Jan W. "Fractal and Multifractal Time Series." In Encyclopedia of Complexity and Systems Science, 3754–79. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-30440-3_221.
Full textKantelhardt, Jan W. "Fractal and Multifractal Time Series." In Encyclopedia of Complexity and Systems Science, 1–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-27737-5_221-3.
Full textIvanova, Kristinka. "Time Series Analysis of Microwave Signals: Multifractal Aspects." In Nano-Crystalline and Thin Film Magnetic Oxides, 283–92. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4493-3_23.
Full textJizba, Petr, and Jan Korbel. "Modeling Financial Time Series: Multifractal Cascades and Rényi Entropy." In Emergence, Complexity and Computation, 227–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45438-7_22.
Full textBouchaud, Jean-Philippe, and Jean-François Muzy. "Financial Time Series: From Batchelier’s Random Walks to Multifractal ‘Cascades’." In Lecture Notes in Physics, 229–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39668-0_11.
Full textJizba, Petr, and Jan Korbel. "Applications of Multifractal Diffusion Entropy Analysis to Daily and Intraday Financial Time Series." In ISCS 2014: Interdisciplinary Symposium on Complex Systems, 333–42. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10759-2_34.
Full textMuñoz-Diosdado, A., and A. M. Aguilar-Molina. "Curvature Analysis of Multifractal Spectra for Time Series of RR Intervals for Patients with Congestive Heart Failure." In IFMBE Proceedings, 49–52. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-10-0266-3_10.
Full textBogachev, Mikhail I., Naiming Yuan, and Armin Bunde. "Fractals and Multifractals in Geophysical Time Series." In Fractals, 231–71. Boca Raton, FL : CRC Press, Taylor & Francis Group, 2017. | “A science publishers book.”: CRC Press, 2017. http://dx.doi.org/10.1201/9781315152264-9.
Full textBanerjee, Santo, M. K. Hassan, Sayan Mukherjee, and A. Gowrisankar. "Fractal and Multifractal in Stochastic Time Series." In Fractal Patterns in Nonlinear Dynamics and Applications, 129–51. CRC Press, 2020. http://dx.doi.org/10.1201/9781315151564-5.
Full textConference papers on the topic "Multifractal time series"
Muñoz-Diosdado, A. "Multifractal Analysis of Time Series." In MODELING OF COMPLEX SYSTEMS: Seventh Granada Lectures. AIP, 2003. http://dx.doi.org/10.1063/1.1571344.
Full textYuan, Ying, and Xin-tian Zhuang. "Multifractal Statistical Analysis of Financial Time Series." In 2006 International Conference on Machine Learning and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icmlc.2006.258580.
Full textGospodinova, Evgeniya. "Time Series Analysis Using Fractal and Multifractal Methods." In CompSysTech '19: 20th International Conference on Computer Systems and Technologies. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3345252.3345265.
Full textZeng, Ming, Xiaonei Zhang, Jinghai Li, and Qinghao Meng. "Multiscale multifractal analysis of near-surface wind speed time series." In 2016 12th World Congress on Intelligent Control and Automation (WCICA). IEEE, 2016. http://dx.doi.org/10.1109/wcica.2016.7578757.
Full textMuñoz D., Alejandro. "Multifractal Analysis of Aging and Complexity in Heartbeat Time Series." In MEDICAL PHYSICS: Eighth Mexican Symposium on Medical Physics. AIP, 2004. http://dx.doi.org/10.1063/1.1811846.
Full textYang, Yujun, Yimei Yang, and Jianping Li. "Role of mean in the multifractal analysis of financial time series." In 2017 14th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). IEEE, 2017. http://dx.doi.org/10.1109/iccwamtip.2017.8301452.
Full textJovanović, Gordana, Svetlana Stanišić, and Mirjana Perišić. "Multifractal Characteristics of Criteria Air Pollutant Time Series in Urban Areas." In Sinteza 2020. Beograd, Serbia: Singidunum University, 2020. http://dx.doi.org/10.15308/sinteza-2020-29-34.
Full textDomingues, Omar D., Philippe Ciuciu, Daria La Rocca, Patrice Abry, and Herwig Wendt. "Multifractal Analysis for Cumulant-Based Epileptic Seizure Detection in Eeg Time Series." In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI). IEEE, 2019. http://dx.doi.org/10.1109/isbi.2019.8759288.
Full textMunoz-Diosdado, A., and J. L. Del Rio-Correa. "Further Study of the Asymmetry for Multifractal Spectra of Heartbeat Time Series." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.260166.
Full textMunoz-Diosdado, A., and J. L. Del Rio-Correa. "Further Study of the Asymmetry for Multifractal Spectra of Heartbeat Time Series." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4397685.
Full textReports on the topic "Multifractal time series"
Derbentsev, V., A. Ganchuk, and Володимир Миколайович Соловйов. Cross correlations and multifractal properties of Ukraine stock market. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1117.
Full textСоловйов, Володимир Миколайович, and О. А. Сердюк. Мультифрактальний аналіз кризових явищ на фондових ринках. Видавець Ткачук О. В., 2015. http://dx.doi.org/10.31812/0564/1159.
Full textSoloviev, Vladimir, Natalia Moiseienko, and Olena Tarasova. Modeling of cognitive process using complexity theory methods. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3609.
Full textСоловйов, Володимир Миколайович, Наталя Володимирівна Моісеєнко, and Олена Юріївна Тарасова. Complexity theory and dynamic characteristics of cognitive processes. Springer, January 2020. http://dx.doi.org/10.31812/123456789/4143.
Full textNechaev, V., Володимир Миколайович Соловйов, and A. Nagibas. Complex economic systems structural organization modelling. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1118.
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