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- V N Smelyanskiy, Dmitri G. Luchinsky, Dogan A. Timucin, Andriy Bandrivskyy
- Physical review. E, Statistical, nonlinear, andâ€¦
- 2005

An algorithm is presented for reconstructing stochastic nonlinear dynamical models from noisy time-series data. The approach is analytical; consequently, the resulting algorithm does not require anâ€¦ (More)

D. G. Luchinsky, 1,2 R. S. Maier, 3,4 R. Mannella, 5 P. V. E. McClintock, 1 and D. L. Stein4,3 1Department of Physics, Lancaster University, Lancaster LA1 4YB, United Kingdom 2Russian Researchâ€¦ (More)

- Igor A Khovanov, Andrey V. Polovinkin, Dmitri G. Luchinsky, V. E. McClintock
- 2013

I. A. Khovanov,1,* A. V. Polovinkin,2 D. G. Luchinsky,3,4 and P. V. E. McClintock3 1School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom 2Radiophysical Department, Nizhnyâ€¦ (More)

- Dmitri G. Luchinsky, Vadim N. Smelyanskiy, Marko Millonas, E. PeterV., McClintock
- 2008

Population fluctuations in a predator-prey system are analyzed for the case where the number of prey could be determined, subject to measurement noise, but the number of predators was unknown. Theâ€¦ (More)

I. A. KHOVANOV, D. G. LUCHINSKY, R. MANNELLA, and P. V. E. McCLINTOCK Department of Physics, Saratov State University, Astrahanskaya 83, 410026, Saratov, Russia Department of Physics, Lancasterâ€¦ (More)

An extended Bayesian inference framework is presented, aiming to infer time-varying parameters in nonstationary nonlinear stochastic dynamical systems. The convergence of the method is discussed. Theâ€¦ (More)

We consider noise-driven exit from a domain of attraction in a two-dimensional bistable system lacking detailed balance. Through analog and digital stochastic simulations, we find a theoreticallyâ€¦ (More)

An extended Bayesian inference framework is presented, aiming to infer time-varying parameters in non-stationary nonlinear stochastic dynamical systems. The convergence of the method is discussed.â€¦ (More)

- Andrea Duggento, Dmitri G. Luchinsky, Vadim N. Smelyanskiy, Igor A Khovanov, Peter V. E. McClintock
- Physical review. E, Statistical, nonlinear, andâ€¦
- 2008

The problem of how to reconstruct the parameters of a stochastic nonlinear dynamical system when they are time-varying is considered in the context of online decoding of physiological informationâ€¦ (More)

- Dmitri G. Luchinsky, Vadim N. Smelyanskiy, Andrea Duggento, Peter V. E. McClintock
- Physical review. E, Statistical, nonlinear, andâ€¦
- 2008

A general Bayesian framework is introduced for the inference of time-varying parameters in nonstationary, nonlinear, stochastic dynamical systems. Its convergence is discussed. The performance of theâ€¦ (More)