606 research outputs found
Dynamical mechanism of anticipating synchronization in excitable systems
We analyze the phenomenon of anticipating synchronization of two excitable
systems with unidirectional delayed coupling which are subject to the same
external forcing. We demonstrate for different paradigms of excitable system
that, due to the coupling, the excitability threshold for the slave system is
always lower than that for the master. As a consequence the two systems respond
to a common external forcing with different response times. This allows to
explain in a simple way the mechanism behind the phenomenon of anticipating
synchronization.Comment: 4 pages including 7 figures. Submitted for publicatio
Computational inference in systems biology
Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs), is a challenging problem. The computational costs associated with repeatedly solving the ODEs are often high. Aimed at reducing this cost, new concepts using gradient matching have been proposed. This paper combines current adaptive gradient matching approaches, using Gaussian processes, with a parallel tempering scheme, and conducts a comparative evaluation with current methods used for parameter inference in ODEs
Delay Induced Excitability
We analyse the stochastic dynamics of a bistable system under the influence
of time-delayed feedback. Assuming an asymmetric potential, we show the
existence of a regime in which the systems dynamic displays excitability by
calculating the relevant residence time distributions and correlation times.
Experimentally we then observe this behaviour in the polarization dynamics of a
vertical cavity surface emitting laser with opto-electronic feedback. Extending
these observations to two-dimensional systems with dispersive coupling we
finally show numerically that delay induced excitability can lead to the
appearance of propagating wave-fronts and spirals.Comment: 5 pages, 6 figure
Construction of an isotropic cellular automaton for a reaction-diffusion equation by means of a random walk
We propose a new method to construct an isotropic cellular automaton
corresponding to a reaction-diffusion equation. The method consists of
replacing the diffusion term and the reaction term of the reaction-diffusion
equation with a random walk of microscopic particles and a discrete vector
field which defines the time evolution of the particles. The cellular automaton
thus obtained can retain isotropy and therefore reproduces the patterns found
in the numerical solutions of the reaction-diffusion equation. As a specific
example, we apply the method to the Belousov-Zhabotinsky reaction in excitable
media
Opção tecnológica para a destruição de plantas de algodão pós-colheita com altas temperaturas: uma revisão
A propensity criterion for networking in an array of coupled chaotic systems
We examine the mutual synchronization of a one dimensional chain of chaotic
identical objects in the presence of a stimulus applied to the first site. We
first describe the characteristics of the local elements, and then the process
whereby a global nontrivial behaviour emerges. A propensity criterion for
networking is introduced, consisting in the coexistence within the attractor of
a localized chaotic region, which displays high sensitivity to external
stimuli,and an island of stability, which provides a reliable coupling signal
to the neighbors in the chain. Based on this criterion we compare homoclinic
chaos, recently explored in lasers and conjectured to be typical of a single
neuron, with Lorenz chaos.Comment: 4 pages, 3 figure
Unstable Dynamics, Nonequilibrium Phases and Criticality in Networked Excitable Media
Here we numerically study a model of excitable media, namely, a network with
occasionally quiet nodes and connection weights that vary with activity on a
short-time scale. Even in the absence of stimuli, this exhibits unstable
dynamics, nonequilibrium phases -including one in which the global activity
wanders irregularly among attractors- and 1/f noise while the system falls into
the most irregular behavior. A net result is resilience which results in an
efficient search in the model attractors space that can explain the origin of
certain phenomenology in neural, genetic and ill-condensed matter systems. By
extensive computer simulation we also address a relation previously conjectured
between observed power-law distributions and the occurrence of a "critical
state" during functionality of (e.g.) cortical networks, and describe the
precise nature of such criticality in the model.Comment: 18 pages, 9 figure
Noise Induced Coherence in Neural Networks
We investigate numerically the dynamics of large networks of globally
pulse-coupled integrate and fire neurons in a noise-induced synchronized state.
The powerspectrum of an individual element within the network is shown to
exhibit in the thermodynamic limit () a broadband peak and an
additional delta-function peak that is absent from the powerspectrum of an
isolated element. The powerspectrum of the mean output signal only exhibits the
delta-function peak. These results are explained analytically in an exactly
soluble oscillator model with global phase coupling.Comment: 4 pages ReVTeX and 3 postscript figure
Border Avoidance: Necessary Regularity for Coefficients and Viscosity Approach
Motivated by the result of invariance of regular-boundary open sets in
\cite{CannarsaDaPratoFrankowska2009} and multi-stability issues in gene
networks, our paper focuses on three closely related aims. First, we give a
necessary local Lipschitz-like condition in order to expect invariance of open
sets (for deterministic systems). Comments on optimality are provided via
examples. Second, we provide a border avoidance (near-viability) counterpart of
\cite{CannarsaDaPratoFrankowska2009} for controlled Brownian diffusions and
piecewise deterministic switched Markov processes (PDsMP). We equally discuss
to which extent Lipschitz-continuity of the driving coefficients is needed.
Finally, by applying the theoretical result on PDsMP to Hasty's model of
bacteriophage (\cite{hasty\_pradines\_dolnik\_collins\_00},
\cite{crudu\_debussche\_radulescu\_09}), we show the necessity of explicit
modeling for the environmental cue triggering lysis
Invariance Conditions for Nonlinear Dynamical Systems
Recently, Horv\'ath, Song, and Terlaky [\emph{A novel unified approach to
invariance condition of dynamical system, submitted to Applied Mathematics and
Computation}] proposed a novel unified approach to study, i.e., invariance
conditions, sufficient and necessary conditions, under which some convex sets
are invariant sets for linear dynamical systems.
In this paper, by utilizing analogous methodology, we generalize the results
for nonlinear dynamical systems. First, the Theorems of Alternatives, i.e., the
nonlinear Farkas lemma and the \emph{S}-lemma, together with Nagumo's Theorem
are utilized to derive invariance conditions for discrete and continuous
systems. Only standard assumptions are needed to establish invariance of
broadly used convex sets, including polyhedral and ellipsoidal sets. Second, we
establish an optimization framework to computationally verify the derived
invariance conditions. Finally, we derive analogous invariance conditions
without any conditions
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