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The paper constructs and studies a generalized model describing two-component systems of reaction – diffusion type with power nonlinearity, considering the influence of external noise. A methodology has been developed for analyzing the generalized model, which includes linear stability analysis, nonlinear stability analysis, and numerical simulation of the system’s evolution. The linear analysis technique uses basic approaches, in which the characteristic equation is obtained using a linearization matrix. Nonlinear stability analysis realized up to third-order moments inclusively. For this, the functions describing the dynamics of the components are expanded in Taylor series up to third-order terms. Then, using the Novikov theorem, the averaging procedure is carried out. As a result, the obtained equations form an infinite hierarchically subordinate structure, which must be truncated at some point. To achieve this, contributions from terms higher than the third order are neglected in both the equations themselves and during the construction of the moment equations. The resulting equations form a set of linear equations, from which the stability matrix is constructed. This matrix has a rather complex structure, making it solvable only numerically. For the numerical study of the system’s evolution, the method of variable directions was chosen. Due to the presence of a stochastic component in the analyzed system, the method was modified such that random fields with a specified distribution and correlation function, responsible for the noise contribution to the overall nonlinearity, are generated across entire layers. The developed methodology was tested on the reaction – diffusion model proposed by Barrio et al., according to the results of the study, they showed the similarity of the obtained structures with the pigmentation of fish. This paper focuses on the system behavior analysis in the neighborhood of a non-zero stationary point. The dependence of the real part of the eigenvalues on the wavenumber has been examined. In the linear analysis, a range of wavenumber values is identified in which Turing instability occurs. Nonlinear analysis and numerical simulation of the system’s evolution are conducted for model parameters that, in contrast, lie outside the Turing instability region. Nonlinear analysis found noise intensities of additive noise for which, despite the absence of conditions for the emergence of diffusion instability, the system transitions to an unstable state. The results of the numerical simulation of the evolution of the tested model demonstrate the process of forming spatial structures of Turing type under the influence of additive noise.

The dynamics of coupled elements’ ensembles are investigated in the context of description of spatio-temporal processes in the myocardium. Basic element is map-based model constructed by simplification and reduction of Luo-Rudy model. In particular, capabilities of the model in replication of different regimes of cardiac activity are shown, including excitable and oscillatory regimes. The dynamics of 1D and 2D lattices of coupled oscillatory elements with a random distribution of individual frequencies are considered. Effects of cluster synchronization and transition to global synchronization by increasing of coupling strength are discussed. Impulse propagation in the chain of excitable cells has been observed. Analysis of 2D lattice of excitable elements with target and spiral waves have been made. The characteristics of the spiral wave has been analyzed in depending on the individual parameters of the map and coupling strength between elements of the lattice. A study of mixed ensembles consisting of excitable and oscillatory elements with a gradient changing of the properties have been made, including the task for description of normal and pathological activity of the sinoatrial node.

This work is devoted to the study of the problem of modeling and analyzing complex oscillatory modes, both regular and chaotic, in systems of interacting populations in the presence of random perturbations. As an initial conceptual deterministic model, a Volterra system of three differential equations is considered, which describes the dynamics of prey populations of two competing species and a predator. This model takes into account the following key biological factors: the natural increase in prey, their intraspecific and interspecific competition, the extinction of predators in the absence of prey, the rate of predation by predators, the growth of the predator population due to predation, and the intensity of intraspecific competition in the predator population. The growth rate of the second prey population is used as a bifurcation parameter. At a certain interval of variation of this parameter, the system demonstrates a wide variety of dynamic modes: equilibrium, oscillatory, and chaotic. An important feature of this model is multistability. In this paper, we focus on the study of the parametric zone of tristability, when a stable equilibrium and two limit cycles coexist in the system. Such birhythmicity in the presence of random perturbations generates new dynamic modes that have no analogues in the deterministic case. The aim of the paper is a detailed study of stochastic phenomena caused by random fluctuations in the growth rate of the second population of prey. As a mathematical model of such fluctuations, we consider white Gaussian noise. Using methods of direct numerical modeling of solutions of the corresponding system of stochastic differential equations, the following phenomena have been identified and described: unidirectional stochastic transitions from one cycle to another, trigger mode caused by transitions between cycles, noise-induced transitions from cycles to the equilibrium, corresponding to the extinction of the predator and the second prey population. The paper presents the results of the analysis of these phenomena using the Lyapunov exponents, and identifies the parametric conditions for transitions from order to chaos and from chaos to order. For the analytical study of such noise-induced multi-stage transitions, the technique of stochastic sensitivity functions and the method of confidence regions were applied. The paper shows how this mathematical apparatus allows predicting the intensity of noise, leading to qualitative transformations of the modes of stochastic population dynamics.

This paper focuses on the problem of modeling and analyzing dynamic regimes, both regular and chaotic, in systems of coupled populations in the presence of random disturbances. The discrete Ricker model is used as the initial deterministic population model. The paper examines the dynamics of two populations coupled by migration. Migration is proportional to the difference between the densities of two populations with a coupling coefficient responsible for the strength of the migration flow. Isolated population subsystems, modeled by the Ricker map, exhibit various dynamic modes, including equilibrium, periodic, and chaotic ones. In this study, the coupling coefficient is treated as a bifurcation parameter and the parameters of natural population growth rate remain fixed. Under these conditions, one subsystem is in the equilibrium mode, while the other exhibits chaotic behavior. The coupling of two populations through migration creates new dynamic regimes, which were not observed in the isolated model. This article aims to analyze the dynamics of corporate systems with variations in the flow intensity between population subsystems. The article presents a bifurcation analysis of the attractors in a deterministic model of two coupled populations, identifies zones of monostability and bistability, and gives examples of regular and chaotic attractors. The main focus of the work is in comparing the stability of dynamic regimes against random disturbances in the migration intensity. Noise-induced transitions from a periodic attractor to a chaotic attractor are identified and described using direct numerical simulation methods. The Lyapunov exponents are used to analyze stochastic phenomena. It has been shown that in this model, there is a region of change in the bifurcation parameter in which, even with an increase in the intensity of random perturbations, there is no transition from order to chaos. For the analytical study of noise-induced transitions, the stochastic sensitivity function technique and the confidence domain method are used. The paper demonstrates how this mathematical tool can be employed to predict the critical noise intensity that causes a periodic regime to transform into a chaotic one.

Population dynamics is considered in a modified chemostat model including diffusion, chemotaxis, and nonlocal competitive losses. To account for influence of the external environment on the population of the ecosystem, a random parameter is included into the model equations. Computer simulations reveal three dynamic modes depending on system parameters: the transition from initial state to a spatially homogeneous steady state, to a spatially inhomogeneous distribution of population density, and elimination of population density.

We consider a time-delayed quadratic discrete model of population dynamics under the influence of random perturbations. Analysis of stochastic attractors of the model is performed using the methods of direct numerical simulation and the stochastic sensitivity function technique. A deformation of the probability distribution of random states around the stable equilibria and cycles is studied parametrically. The phenomenon of noise-induced transitions in the zone of discrete cycles is demonstrated.

Our purpose is to study the spatio-temporal population wave behavior observed in the predator-prey system. It is assumed that predators move both directionally and randomly, and prey spread only diffusely. The model does not take into account demographic processes in the predator population; it’s total number is constant and is a parameter. The variables of the model are the prey and predator densities and the predator speed, which are connected by a system of three reaction – diffusion – advection equations. The system is considered on an annular range, that is the periodic conditions are set at the boundaries of the interval. We have studied the bifurcations of wave modes arising in the system when two parameters are changed — the total number of predators and their taxis acceleration coefficient.

The main research method is a numerical analysis. The spatial approximation of the problem in partial derivatives is performed by the finite difference method. Integration of the obtained system of ordinary differential equations in time is carried out by the Runge –Kutta method. The construction of the Poincare map, calculation of Lyapunov exponents, and Fourier analysis are used for a qualitative analysis of dynamic regimes.

It is shown that, population waves can arise as a result of existence of directional movement of predators. The population dynamics in the system changes qualitatively as the total predator number increases. А stationary homogeneous regime is stable at low value of parameter, then it is replaced by self-oscillations in the form of traveling waves. The waveform becomes more complicated as the bifurcation parameter increases; its complexity occurs due to an increase in the number of temporal vibrational modes. A large taxis acceleration coefficient leads to the possibility of a transition from multi-frequency to chaotic and hyperchaotic population waves. A stationary regime without preys becomes stable with a large number of predators.

We study the stochastic dynamics of the two-dimensional Hindmarsh–Rose model in the parametrical zone of coexisting stable equilibria and limit cycles. The phenomenon of noise-induced transitions between the attractors is investigated. Under the random disturbances, equilibrium and periodic regimes combine in bursting regime: the system demonstrates an alternation of small fluctuations near the equilibrium with high amplitude oscillations. This effect is analysed using the stochastic sensitivity function technique and a method of estimation of critical values for noise intensity is proposed.

We consider “predator – prey” model taking into account the competition of prey, predator for different from the prey resources, and their interaction described by the second type Holling trophic function. An analysis of the attractors is carried out depending on the coefficient of competition of predators. In the deterministic case, this model demonstrates the complex behavior associated with the local (Andronov –Hopf and saddlenode) and global (birth of a cycle from a separatrix loop) bifurcations. An important feature of this model is the disappearance of a stable cycle due to a saddle-node bifurcation. As a result of the presence of competition in both populations, parametric zones of mono- and bistability are observed. In parametric zones of bistability the system has either coexisting two equilibria or a cycle and equilibrium. Here, we investigate the geometrical arrangement of attractors and separatrices, which is the boundary of basins of attraction. Such a study is an important component in understanding of stochastic phenomena. In this model, the combination of the nonlinearity and random perturbations leads to the appearance of new phenomena with no analogues in the deterministic case, such as noise-induced transitions through the separatrix, stochastic excitability, and generation of mixed-mode oscillations. For the parametric study of these phenomena, we use the stochastic sensitivity function technique and the confidence domain method. In the bistability zones, we study the deformations of the equilibrium or oscillation regimes under stochastic perturbation. The geometric criterion for the occurrence of such qualitative changes is the intersection of confidence domains and the separatrix of the deterministic model. In the zone of monostability, we evolve the phenomena of explosive change in the size of population as well as extinction of one or both populations with minor changes in external conditions. With the help of the confidence domains method, we solve the problem of estimating the proximity of a stochastic population to dangerous boundaries, upon reaching which the coexistence of populations is destroyed and their extinction is observed.

The article considers a bilinear model of the influence of external disturbances on the stability of the structure of social systems. Approaches to the third-party stabilization of the initial system consisting of two groups are investigated — by reducing the initial system to a linear system with uncertain parameters and using the results of the theory of linear dynamic games with a quadratic criterion. The influence of the coefficients of the proposed model of the social system and the control parameters on the quality of the system stabilization is analyzed with the help of computer experiments. It is shown that the use of a minimax strategy by a third party in the form of feedback control leads to a relatively close convergence of the population of the second group (excited by external influences) to an acceptable level, even with unfavorable periodic dynamic perturbations.

The influence of one of the key coefficients in the criterion $(\varepsilon)$ used to compensate for the effects of external disturbances (the latter are present in the linear model in the form of uncertainty) on the quality of system stabilization is investigated. Using Z-transform, it is shown that a decrease in the coefficient $\varepsilon$ should lead to an increase in the values of the sum of the squares of the control. The computer calculations carried out in the article also show that the improvement of the convergence of the system structure to the equilibrium level with a decrease in this coefficient is achieved due to sharp changes in control in the initial period, which may induce the transition of some members of the quiet group to the second, excited group.

The article also examines the influence of the values of the model coefficients that characterize the level of social tension on the quality of management. Calculations show that an increase in the level of social tension (all other things being equal) leads to the need for a significant increase in the third party's stabilizing efforts, as well as the value of control at the transition period.

The results of the statistical modeling carried out in the article show that the calculated feedback controls successfully compensate for random disturbances on the social system (both in the form of «white» noise, and of autocorrelated disturbances).