Multilevel time series complexity

• Autorzy: Kozarzewski B.
• Języki publikacji: EN

Abstrakty

EN

A simple and fast algorithm to quantify time series complexity which follows newly developed nonparametric complexity measure of symbolic sequences is proposed. In order to get complexity measure over many time scales I suggest using wavelets multilevel decomposition of time series instead of coarse-graining. As an example multilevel complexity of series generated by Henon map, as well as some data downloaded from PhysioBank database: synthetic series, gait dynamics, and interbeat heart rate is calculated.

Słowa kluczowe

EN

complexity; wavelets decomposition; biomedical signals

PL

dekompozycja falkowa; sygnał biomedyczny

• Wydawca: Wydawnictwo Politechniki Łódzkiej
• Czasopismo: Journal of Applied Computer Science
• Rocznik: 2011
• Tom: Vol. 19, nr 2
• Strony: 61--71
• Opis fizyczny: Bibliogr. 10 poz.

Twórcy

autor

Kozarzewski B.

• University of Information Technology and Management Faculty of Applied Computer Science H. Sucharskiego 2, 35-225 Rzeszów, Poland,

Bibliografia

• [1] Rajkovič, M., Entropic nonextensivity as a measure of time series complexity, [on-line]. Access:ArXiv:nlin/00404019v1, 2004, /[2010-12-01].
• [2] Costa, M., Peng, C.-K., Goldberg, A. L., and Hausdorff, J. M., Multiscale entropy analysis of human gait dynamics, Physica A, Vol. 330, 2003, pp. 53- 60.
• [3] Costa, M., Goldberg, A. L., and Peng, C.-K., Multiscale entropy analysis of biological signals, Physical Review E, Vol. 71, No. 2, 2005, pp. 021906-1- 021906-17.
• [4] Pincus, S. M., Assessing serial irregularity and its implications for health, Annales N Y Acad. Sci., 2001, pp. 245-267.
• [5] Ke, D.-G. and Tong, Q.-Y., Easily adaptable complexity measure for finite time series, Physical Review E, Vol. 77, No. 5, 2008, pp. 066215-1 - 066215-8.
• [6] Lempel, A. and Ziv, J., On the complexity of finite sequences, IEEE Trans. Inform. Theor., Vol. IT-22, 1976, pp. 75-81.
• [7] PhysioBank, Tech. rep., PhysioBank Archive Index, [on-line]. Access: http://wwww.physionet.org, /[2010-12-01].
• [8] Scilab-5.0.3, Tech. rep., Consortium Scilab (INRIA, ENPC), [on-line]. Access: http://wwww.scilab.org, /[2010-12-01].
• [9] Xu, L., Ivanov, P. C., Hu, K., Carbone, A., and Stanley, H. E., Quantifying signals with power-law correlations, Physical Review E, Vol. 71, No. 5, 2005, pp. 051101-1 - 051101-14.
• [10] Scafetta, N., Griffin, L., and West, B. J., Holder exponent spectra for human gait, Physica A, Vol. 328, 2003, pp. 561-583.