Consider the stochastic Duffing-van der Pol equation ẍ = −ω2x− Ax −Bx2ẋ + εβẋ + εσxẆt with A ≥ 0 and B > 0. If β/2 + σ/8ω > 0 then for small enough ε > 0 the system (x, ẋ) is positive recurrent in R \ {0}. Let λ̃ε denote the top Lyapunov exponent for the linearization of this equation along trajectories. The main result asserts that λ̃ε ∼ ελ̃ as ε → 0 where λ̃ is the top Lyapunov exponent along tra...

Fine-scale models such as stochastic master equations can provide a very accurate description of the real genetic regulatory system but inadequate time series data and limitations on cell specific measurements in biological experiments prevent the accurate inference of the parameters of such a fine-scale model. Furthermore, the use of fine-scale stochastic models is restricted by the inherent c...

The objective of this study was to model seasonal behavior of broiler price in Iran that can be used to forecast the monthly broiler prices. In this context, the periodic autoregressive (PAR), the seasonal integrated models, and the Box-Jenkins (SARIMA) models were used as the primary nominates for the forecasting model. It was shown that the PAR (q) model could not be considered as an appropri...

We assessed the benefits of vaccination against Mycobacterium avium subsp. paratuberculosis (MAP) on the average daily milk yield (DMY) of sheep and goat flocks. A stochastic simulation model was used to estimate the DMY pre and post vaccination of the flock replacements. The average DMY increased steadily for the first ten years post vaccination and then reached a plateau. Medians for the DMY ...

gravitational search algorithm (gsa) is one of the newest swarm based optimization algorithms, which has been inspired by the newtonian laws of gravity and motion. gsa has empirically shown to be an efficient and robust stochastic search algorithm. since introducing gsa a convergence analysis of this algorithm has not yet been developed. this paper introduces the first attempt to a formal conve...

It is common practice in structural dynamics to develop mathematical models for system behavior, and wa are now capable of developing stochastic models, i.e., models whose parameters are random variables. Such models have random characteristics that are meant to simulate the randomness in characteristics of experimentally observed systems. This paper suggests a formal stat ist ical procedure fo...

We introduce stochastic and quantum finite-state transducers as representations of classical stochastic and quantum finitary processes. Formal process languages serve as the literal representation of the behavior of these processes and are recognized and generated by subclasses of stochastic and quantum transducers. We compare deterministic and nondeterministic stochastic and quantum automata, ...

Neurons in the brain express intrinsic dynamic behavior which is known to be stochastic in nature. A crucial question in building models of neuronal excitability is how to be able to mimic the dynamic behavior of the biological counterpart accurately and how to perform simulations in the fastest possible way. The well-established Hodgkin-Huxley formalism has formed to a large extent the basis f...

in this paper, a high-order and conditionally stable stochastic difference scheme is proposed for the numerical solution of $rm ithat{o}$ stochastic advection diffusion equation with one dimensional white noise process. we applied a finite difference approximation of fourth-order for discretizing space spatial derivative of this equation. the main properties of deterministic difference schemes,...