Detecting limit cycles in stochastic time series
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Detecting limit cycles in stochastic time series. / Martiny, Emil S.; Jensen, Mogens H.; Heltberg, Mathias S.
In: Physica A: Statistical Mechanics and its Applications, Vol. 605, 127917, 17.02.2022.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Detecting limit cycles in stochastic time series
AU - Martiny, Emil S.
AU - Jensen, Mogens H.
AU - Heltberg, Mathias S.
N1 - Publisher Copyright: © 2022
PY - 2022/2/17
Y1 - 2022/2/17
N2 - The emergence of oscillatory behaviour represents fundamental information about the interactions of the underlying system. In biological systems, oscillations have been observed in experimental data, but due to the significant level of noise, it is difficult to characterize whether observed dynamics based on time series, are truly limit cycles. Here, we present a simple three step method to identify the presence of limit cycles in stochastic systems. Considering input from one-dimensional time series, as are typically obtained in experiments, we propose statistical measures to detect the existence of limit cycles. This is tested on models from chemical networks, and we investigate how the underlying dynamics can be separated depending on the noise level and length of the series.
AB - The emergence of oscillatory behaviour represents fundamental information about the interactions of the underlying system. In biological systems, oscillations have been observed in experimental data, but due to the significant level of noise, it is difficult to characterize whether observed dynamics based on time series, are truly limit cycles. Here, we present a simple three step method to identify the presence of limit cycles in stochastic systems. Considering input from one-dimensional time series, as are typically obtained in experiments, we propose statistical measures to detect the existence of limit cycles. This is tested on models from chemical networks, and we investigate how the underlying dynamics can be separated depending on the noise level and length of the series.
KW - Limit cycles
KW - Oscillations
KW - Statistical test
KW - Stochastic dynamics
U2 - 10.1016/j.physa.2022.127917
DO - 10.1016/j.physa.2022.127917
M3 - Journal article
AN - SCOPUS:85135690793
VL - 605
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
SN - 0378-4371
M1 - 127917
ER -
ID: 343301816