Desynchronization of large scale delayed neural networks

We consider a ring of identical neurons with delayed nearest neighborhood inhibitory interaction. Under general conditions, such a network has a slowly oscillatory synchronous periodic solution which is completely characterized by a scalar delay differential equation with negative feedback. Despite the fact that the slowly oscillatory periodic solution of the scalar equation is stable, we show that the associated synchronous solution is unstable if the size of the network is large.

     

Implementation and stability study of phase-locked-loop nonlinear dynamic measurement systems

We study the stability and convergence of a phase-locked-loop applied to a nonlinear system. It has been shown through numerical simulations by previous investigators that nonlinearity gives rise to oscillatory instability. By applying the method of averaging to the nonlinear system, we found that the nonlinear system has the identical criterion for stability as the linear system. However, the stable equilibrium has a shrinking domain of attraction as the nonlinearity increases. We show this by examining the feedback function. Moreover, we propose a nonlinear feedback which has faster convergence rate.     

Stochastic encoding in sensory neurons: impulse patterns of mammalian cold receptors

Intrinsic oscillations at the level of the membrane potential are a widespread feature of nerve cells. Several evidences exist that, in particular, sensory neurons combine their oscillatory membrane potentials with intrinsic, membrane and/or synaptic noise to obtain sensitive encoding properties. An interesting example are mammalian cold receptors where stimulus transduction results from modulation of intrinsic receptor oscillations with essential contribution of noise thereby generating a rich spectrum of impulse patterns. To further explore the dynamics of these receptors we here investigate an HH-type model for oscillations and spike initiation in cold receptors. By use of a biophysically plausible temperature scaling and with addition of noise, the model successfully mimicks the principle temperature-dependence of stationary impulse patterns of real cold receptors. Our results suggest that interactions between stochastic and deterministic dynamics are of functional importance for the encoding charcteristics of cold receptors.     

Stabilization of Stochastic Hybrid Linear Systems with Noise

Abstract

This article deals with the class of uncertain stochastic hybrid linear systems with noise. The uncertainties we are considering are of norm bounded type. The stochastic stabilization and robust stabilization problems are treated. Linear matrix inequality (LMI)-based sufficient conditions are developed to design the state feedback controller with constant gain that stochastically (robust stochastically) stabilizes the studied class of systems. Our results are mode independent and require only the complete access to the state vector. Numerical examples are given to show the effectiveness of the proposed results.     

The Poincaré Map of Randomly Perturbed Periodic Motion

A system of autonomous differential equations with a stable limit cycle and perturbed by small white noise is analyzed in this work. In the vicinity of the limit cycle of the unperturbed deterministic system, we define, construct, and analyze the Poincaré map of the randomly perturbed periodic motion. We show that the time of the first exit from a small neighborhood of the fixed point of the map, which corresponds to the unperturbed periodic orbit, is well approximated by the geometric distribution. The parameter of the geometric distribution tends to zero together with the noise intensity. Therefore, our result can be interpreted as an estimate of the stability of periodic motion to random perturbations. In addition, we show that the geometric distribution of the first exit times translates into statistical properties of solutions of important differential equation models in applications. To this end, we demonstrate three distinct examples from mathematical neuroscience featuring complex oscillatory patterns characterized by the geometric distribution. We show that in each of these models the statistical properties of emerging oscillations are fully explained by the general properties of randomly perturbed periodic motions identified in this paper.     

Long-time behavior of solutions to a class of stochastic parabolic equations with homogeneous white noise: itô's case

In this article we prove new results concerning the long-time behaviour of random fields that are solutions in some generalized sense to a class of semilinear parabolic equations subjected to a homogeneous and multiplicative white noise. Our main results state that these random fields eventually converge with probability. one to a global attractor represented by a single random variable whose properties we investigate in detail. We analyze the partial differential equations of this article in light Itô's stochastic calculus and thereby obtain stabilization and stability results which are substantially different from our earlier results concerning their interpretation in the sense of Stratonovitch. In particular, the asymptotic properties of the random fields that we investigate here exhibit no recurrence and oscillatory properties     

Bifurcation analysis of delay-induced periodic oscillations

In this paper we consider a generic differential equation with a cubic nonlinearity and delay. This system, in the absence of delay, is known to undergo an oscillatory instability. The addition of the delay is shown to result in the creation of a number of periodic solutions with constant amplitude and a constant frequency; the number of solutions increases with the size of the delay. Indeed, for many physical applications in which oscillatory instabilities are induced by a delayed response or feedback mechanism, the system under consideration forms the underlying backbone for a mathematical model. Our study showcases the effectiveness of performing a numerical bifurcation analysis, alongside the use of analytical and geometrical arguments, in investigating systems with delay. We identify curves of codimension-one bifurcations of periodic solutions. We show how these curves interact via codimension-two bifurcation points: double singularities which organise the bifurcations and dynamics in their local vicinity.     

Forward–backward stochastic differential equations with monotone functionals and mean field games with common noise

We consider a system of forward–backward stochastic differential equations (FBSDEs) with monotone functionals. We show that such a system is well-posed by the method of continuation similarly to Peng and Wu (1999) for classical FBSDEs. As applications, we prove the well-posedness result for a mean field FBSDE with conditional law and show the existence of a decoupling function. Lastly, we show that mean field games with common noise are uniquely solvable under a linear-convex setting and weak-monotone cost functions and prove that the optimal control is in a feedback form depending only on the current state and conditional law.     

Oscillation and nonoscillation of perturbed nonlinear equations with p-Laplacian

In this paper, we analyze oscillatory properties of perturbed half-linear differential equations (i.e., equations with one-dimensional p-Laplacian). The presented research covers the Euler and Riemann–Weber type equations with very general coefficients. We prove an oscillatory result and a nonoscillatory one, which show that the studied equations are conditionally oscillatory (i.e., there exists a certain threshold value that separates oscillatory and nonoscillatory equations). The obtained criteria are easy to use. Since the number of perturbations is arbitrary, we solve the oscillation behavior of the equations in the critical setting when the coefficients give exactly the threshold value. The results are new for linear equations as well.     

On abstract stochastic bilinear equations with white noise inputs

We study the response of a class of stochastic bilinear hyperbolic (oscillatory) systems to multiplicative noise inputs. We formulate them as bilinear abstract Cauchy problems in the framework of (finitely additive) white noise theory. We show that the solution can be expressed in terms of the integral of the noise, which enables us to study relevant stochastic properties of the solution.     

Synchronization of chaotic dynamical network with unknown generally time-delayed couplings via a simple adaptive feedback control

In this paper, based on the principle of functional differential equations, a simple adaptive feedback controller is proposed to synchronize the network with unknown generally time-delayed coupling functions. Unlike the other control schemes, we design the controllers by the output of each node. The advantage of this scheme is that we need not to know the concrete structure of coupling functions or a solution of node system in advance. Moreover, an illustrative example is considered and numerical simulations are performed to demonstrate the effectiveness of this control scheme. The numerical simulation results show that our method is valid and robust against the weak noise.     

Stability,coherent spiking and synchronization in noisy excitable systems with coupling and internal delays

We study the onset and the adjustment of different oscillatory modes in a system of excitable units subjected to two forms of noise and delays cast as external or internal according to whether they are associated with inter- or intra-unit activity. Conditions for stability of a single unit are derived in case of the linearized perturbed system, whereas the interplay of noise and internal delay in shaping the oscillatory motion is analyzed by the method of statistical linearization. It is demonstrated that the internal delay, as well as its coaction with external noise, drive the unit away from the bifurcation controlled by the excitability parameter. For the pair of interacting units, it is shown that the external/internal character of noise primarily influences frequency synchronization and the competition between the noise-induced and delay-driven oscillatory modes, while coherence of firing and phase synchronization substantially depend on internal delay. Some of the important effects include: (i) loss of frequency synchronization under external noise; (ii) existence of characteristic regimes of entrainment, where under variation of coupling delay, the optimized unit (noise intensity fixed at resonant value) may be controlled by the adjustable unit (variable noise) and vice versa, or both units may become adjusted to coupling delay; (iii) phase synchronization achieved both for noise-induced and delay-driven modes.     

Spectral stability results for higher-order operators under perturbations of the domain

We analyze the spectral behavior of higher-order elliptic operators when the domain is perturbed. We provide general spectral stability results for Dirichlet and Neumann boundary conditions. Moreover, we study the bi-harmonic operator with the so-called intermediate boundary conditions. We give special attention to this last case and analyze its behavior when the boundary of the domain has some oscillatory behavior. We will show that there is a critical oscillatory behavior and that the limit problem depends on whether we are above, below or just sitting on this critical value.     

Robust synchronization of chaotic non-autonomous systems using adaptive-feedback control

In this paper, we apply the simple adaptive-feedback control scheme to synchronize a class of chaotic non-autonomous systems. Based on the invariance principle of differential equations, some generic sufficient conditions for global asymptotic synchronization are obtained. Unlike the usual linear feedback, the variable feedback strength is automatically adapted to completely synchronize two identical systems and simple to implement in practice. As illustrative examples, synchronization of two parametrically excited chaotic pendulums and that of two 4D new systems are considered here. Numerical simulations show the proposed method is effective and robust against the effect of noise.     

Exclusion sensitivity of Boolean functions

Recently the study of noise sensitivity and noise stability of Boolean functions has received considerable attention. The purpose of this paper is to extend these notions in a natural way to a different class of perturbations, namely those arising from running the symmetric exclusion process for a short amount of time. In this study, the case of monotone Boolean functions will turn out to be of particular interest. We show that for this class of functions, ordinary noise sensitivity and noise sensitivity with respect to the complete graph exclusion process are equivalent. We also show this equivalence with respect to stability. After obtaining these fairly general results, we study “exclusion sensitivity” of critical percolation in more detail with respect to medium-range dynamics. The exclusion dynamics, due to its conservative nature, is in some sense more physical than the classical i.i.d. dynamics. Interestingly, we will see that in order to obtain a precise understanding of the exclusion sensitivity of percolation, we will need to describe how typical spectral sets of percolation diffuse under the underlying exclusion process.     

Trajectory Segmentation and Symbolic Representation of Dynamics of Delayed Recurrent Inhibitory Neural Loops

We develop a general symbolic dynamics framework to examine the dynamics of an analogue of the integrate-and-fire neuron model of recurrent inhibitory loops with delayed feedback, which incorporates the firing procedure and absolute refractoriness. We first show that the interaction of the delay, the inhibitory feedback and the absolute refractoriness can generate three basic types of oscillations, and these oscillations can be pinned together to form interesting coexisting periodic patterns in the case of short feedback duration. We then develop a natural symbolic dynamics formulation for the segmentation of a typical trajectory in terms of the basic oscillatory patterns, and use this to derive general principles that determine whether a periodic pattern can and should occur.     

强迫二阶非线性泛函微分方程解的振动性与渐近性

本文讨论强迫二阶非线性泛函微分方程（ａ（ｔ）ｘ＇（ｔ））＇＋ｐ（ｔ）ｆ（ｘ（ｔ），ｘ（ｑ（ｔ）））＝ｒ（ｔ）解的振动性与渐近性。所得结论改进和推广了已知的一些结果。     

Nonlinear oscillations in business cycle model with time lags

In this paper we analyse the dynamics of the Kaldor–Kalecki business cycle model. This model is based on the classical Kaldor model in which capital stock changes are caused by past investment decisions. This lag is connected with time delay needed for new capital to be installed. The dynamics of the model is reduced to the form of damped oscillator with negative feedback connected with lag parameter and next it is analysed in terms of bifurcation theory. We find conditions for existence and persistence of oscillatory behaviour which is represented by limit cycle on some central manifold in phase space, i.e., single Hopf bifurcation. We demonstrate that the Hopf cycles may be exhibited for nonzero measure set of the parameter space. The conditions for bifurcation of co-dimension two connected with interaction of bifurcations as well as bifurcation diagrams are also given. Finally, we obtain numerical values describing an amplitude and a period of oscillation for different parameter of the system. It is also proved that while the investment function is not nonlinear a quasi-periodic solution (a 1:2 resonant double Hopf point) can appear. The source of such a behaviour is rather a consequence of time lag than nonlinearity of the investment function. Our results confirm the existence of asymmetric (two periodic) cycles in the Kaldor–Kalecki model with time-to-build.