Modified Bayesian approach for the reconstruction of dynamical systems from time series

Mukhin, Dmitry; Feǐgin, A. M.; Loskutov, Evgeny; Molkov, Ya. I.

doi:10.1103/physreve.73.036211

Cited by 21 publications

(11 citation statements)

References 9 publications

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“…The likelihood (equation 3) was sampled using Markov Chain Monte Carlo approach by Metropolis–Hastings algorithm (Mukhin et al. ; Loskutov et al. ; Molkov et al.…”

Section: Methodsmentioning

confidence: 99%

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Amphetamine enhances endurance by increasing heat dissipation

et al. 2016

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Athletes use amphetamines to improve their performance through largely unknown mechanisms. Considering that body temperature is one of the major determinants of exhaustion during exercise, we investigated the influence of amphetamine on the thermoregulation. To explore this, we measured core body temperature and oxygen consumption of control and amphetamine‐trea ted rats running on a treadmill with an incrementally increasing load (both speed and incline). Experimental results showed that rats treated with amphetamine (2 mg/kg) were able to run significantly longer than control rats. Due to a progressively increasing workload, which was matched by oxygen consumption, the control group exhibited a steady increase in the body temperature. The administration of amphetamine slowed down the temperature rise (thus decreasing core body temperature) in the beginning of the run without affecting oxygen consumption. In contrast, a lower dose of amphetamine (1 mg/kg) had no effect on measured parameters. Using a mathematical model describing temperature dynamics in two compartments (the core and the muscles), we were able to infer what physiological parameters were affected by amphetamine. Modeling revealed that amphetamine administration increases heat dissipation in the core. Furthermore, the model predicted that the muscle temperature at the end of the run in the amphetamine‐treated group was significantly higher than in the control group. Therefore, we conclude that amphetamine may mask or delay fatigue by slowing down exercise‐induced core body temperature growth by increasing heat dissipation. However, this affects the integrity of thermoregulatory system and may result in potentially dangerous overheating of the muscles.

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“…The likelihood (equation 3) was sampled using Markov Chain Monte Carlo approach by Metropolis–Hastings algorithm (Mukhin et al. ; Loskutov et al. ; Molkov et al.…”

Section: Methodsmentioning

confidence: 99%

“…where k = saline or Amph, and N = 13 and 15 for saline and Amph, respectively. The likelihood (equation 3) was sampled using Markov Chain Monte Carlo approach by Metropolis-Hastings algorithm (Mukhin et al 2006;Loskutov et al 2008;Molkov et al 2011Molkov et al , 2012Robert et al).…”

Section: Model Parameter Estimationmentioning

confidence: 99%

Amphetamine enhances endurance by increasing heat dissipation

et al. 2016

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“…Construction of parametrized models (global reconstruction) of deterministic dynamical systems from time series has been broadly discussed in the literature in the past 20 years [1][2][3][4][5][6][7][8][9][10]. The mathematical apparatus substantiating such a possibility has been developed.…”

Section: Introductionmentioning

confidence: 99%

Random dynamical models from time series

et al. 2012

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In this work we formulate a consistent Bayesian approach to modeling stochastic (random) dynamical systems by time series and implement it by means of artificial neural networks. The feasibility of this approach for both creating models adequately reproducing the observed stationary regime of system evolution, and predicting changes in qualitative behavior of a weakly nonautonomous stochastic system, is demonstrated on model examples. In particular, a successful prognosis of stochastic system behavior as compared to the observed one is illustrated on model examples, including discrete maps disturbed by non-Gaussian and nonuniform noise and a flow system with Langevin force.

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“…Such problems can involve prediction of the qualitative variations in the dynamics [5,6] and estimation of the characteristics of interaction (coupling) among the complex-system elements [7][8][9]. Along with the deterministic nonlinear models [1][2][3], much attention is given to the development of the stochastic model equations [3][4][5][6][10][11][12][13] also when estimating the directional-coupling characteristics by empirical simulation of the phase dynamics [8,14]. The issue of the presence or absence of delay of the mutual influence of the studied systems and of the delay-time value [17], which often determines the observed-dynamics complexity, is important when solving the above-mentioned problem that is topical in neurophysiology [15], climatology [16], and other fields.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Characteristics of Delayed Coupling Between Stochastic Oscillators from the Observed Phase Dynamics

Sidak

Смирнов

Безручко

2015

Radiophys Quantum El

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UDC 530.18A method for estimating the characteristics of the delayed coupling between the oscillatory systems, which is based on the empirical simulation of the phase dynamics with allowance for the phase-noise correlatedness, is proposed. The method efficiency is illustrated FOR the standard stochastic and chaotic oscillators in numerical experiments. Using this method for analyzing climatic time series, we confirm the presence of the delayed influence of the El Niño Southern oscillation on the North Atlantic Oscillation.

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Modified Bayesian approach for the reconstruction of dynamical systems from time series

Cited by 21 publications

References 9 publications

Amphetamine enhances endurance by increasing heat dissipation

Amphetamine enhances endurance by increasing heat dissipation

Random dynamical models from time series

Estimation of Characteristics of Delayed Coupling Between Stochastic Oscillators from the Observed Phase Dynamics

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