Abstract:We consider an effect of random disturbances on the generalized logistic model with delay in mono- and bistable regimes near Neimark–Sacker bifurcation. Noise-induced transitions between coexisting attractors, and between separate parts of the unique attractor, are studied. We suggest a semi-analytical approach that combines a geometric analysis of the mutual arrangement of attractors, their basins of attraction, and corresponding confidence domains found by the stochastic sensitivity functions technique. Cons… Show more
“…This extended model possesses a coexistence of the equilibrium and cycle, or two stable cycles (birhythmicity). The aim of the present paper is to study effects of noise in this bistable model and show how stochastic phenomena can be investigated with the help of the analytical approach based on the stochastic sensitivity technique [54][55][56].…”
A mathematical model of the biochemical reaction with nonlinear recycling of the product into substrate is considered. The main control parameter of this model is the substrate injection rate, which is subject to random disturbances. We study noise-induced oscillations in the parameter zones where the system is bistable and exhibit a coexistence of the equilibrium and limit cycle, or two stable cycles (birhythmicity). Phenomena of the generation of noisy birhythmicity and 'stochastic preference' of attractors are studied on the basis of the stochastic sensitivity function technique, confidence domains method, and statistics of interspike intervals.
“…This extended model possesses a coexistence of the equilibrium and cycle, or two stable cycles (birhythmicity). The aim of the present paper is to study effects of noise in this bistable model and show how stochastic phenomena can be investigated with the help of the analytical approach based on the stochastic sensitivity technique [54][55][56].…”
A mathematical model of the biochemical reaction with nonlinear recycling of the product into substrate is considered. The main control parameter of this model is the substrate injection rate, which is subject to random disturbances. We study noise-induced oscillations in the parameter zones where the system is bistable and exhibit a coexistence of the equilibrium and limit cycle, or two stable cycles (birhythmicity). Phenomena of the generation of noisy birhythmicity and 'stochastic preference' of attractors are studied on the basis of the stochastic sensitivity function technique, confidence domains method, and statistics of interspike intervals.
“…Our analytical approach is based on the stochastic sensitivity technique and confidence domains approximating dispersion of random states around deterministic attractors. 46,47 Mathematical details of this general technique are briefly discussed in Appendix C1. In Section 2, we give an overview of deterministic corporate dynamics of coupled chaotic oscillators depending on the increasing strength of coupling and discuss the variety of attractors and bifurcations.…”
Stochastic effects in corporate dynamics of two symmetrically coupled chaotic oscillators are studied. As a functional unit, we use a discrete system defined by the logistic map. It is shown that increasing coupling parameter changes corporate deterministic dynamics and causes transitions "chaos-order-chaos." We study an order window between Neimark-Sacker and crisis bifurcation points and show how this window is contracted and eliminated by increasing noise.For parametric analysis of these stochastic phenomena in coupled system, we apply the method of confidence domains based on the mathematical theory of stochastic sensitivity.
“…A mathematical analysis of these phenomena requires analysing the saddle-node, period-doubling, crisis, and Neimark-Sacker bifurcations [8,9,10]. A presence of inevitable noise can cause another, more complicated, regimes [11,12,13,14,15,16].…”
A nonlinear dynamical model of two coupled neurons based on the Rulkov map is considered. Variability analysis of corporate dynamics depending on the type of activity of separated neurons and strength of coupling is performed. Transitions between stationary, periodic, quasiperiodic, and chaotic regimes of this neuron system are studied. Additional effects of random disturbances on this system are discussed. Noise-induced transitions between periodic and chaotic stochastic oscillations are demonstrated.
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