• Korean Journal of Mathematics
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• v.24 no.3
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• pp.447-467
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• 2016

We prove the existence of random attractors for the continuous random dynamical systems generated by stochastic damped plate equations with linear memory and additive white noise when the nonlinearity has a critically growing exponent.

• Korean Journal of Mathematics
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• v.26 no.4
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• pp.583-599
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• 2018

In this paper, we are concerned with the existence of random dynamics for stochastic non-autonomous reaction-diffusion equations driven by a Wiener-type multiplicative noise defined on the unbounded domains.

• Journal of the Korean Mathematical Society
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• v.60 no.2
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• pp.255-271
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• 2023

In this paper, we deal with random attractors for dynamical systems forced by a deterministic noise. These kind of systems are modeled as skew products where the dynamics of the forcing process are described by the base transformation. Here, we consider skew products over the Bernoulli shift with the unit interval fiber. We study the geometric structure of maximal attractors, the orbit stability and stability of mixing of these skew products under random perturbations of the fiber maps. We show that there exists an open set U in the space of such skew products so that any skew product belonging to this set admits an attractor which is either a continuous invariant graph or a bony graph attractor. These skew products have negative fiber Lyapunov exponents and their fiber maps are non-uniformly contracting, hence the non-uniform contraction rates are measured by Lyapnnov exponents. Furthermore, each skew product of U admits an invariant ergodic measure whose support is contained in that attractor. Additionally, we show that the invariant measure for the perturbed system is continuous in the Hutchinson metric.

• Computational Structural Engineering
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• v.10 no.4
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• pp.239-249
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• 1997

The method to distinguish chaotic attractors in the perturbed response behaviors of a piecewise-linear system under combined regular and external randomness is provided and examined. In the noisy fields such as the ocean environment, excitation forces induced by wind, waves and currents contain a finite degree of randomness. Under external random perturbations, the system responses are disturbed, and consequently chaotic signatures in the response attractors are not distinguishable, but rather look just random-like. Mean Poincare map can be utilized to identify such chaotic responses veiled due to the random noise by averaging the noise effect out of the perturbed responses. In this study, the procedure to create mean Poincare map combined with the direct numerical simulations is provided and examined. It is found that mean Poincare maps can successfully distinguish chaotic attractors under stochastic excitations, and also can give the information of limit value of noise intensity with which the chaos signature in system responses vanishes.

• Bulletin of the Korean Mathematical Society
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• v.41 no.2
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• pp.327-335
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• 2004

In this paper, we reformulate a snapshot attractor([5]), ($K,\;\={\mu_{\iota}}$) generated by a random baker's map with a sequence of probability measures {\={\mu_{\iota}}} on K. We obtain bounds of the correlation dimensions of ($K,\;\={\mu_{\iota}}$) for all ${\iota}\;{\geq}\;1$.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.3
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• pp.138-146
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• 2010

It is well known that many biological networks are very robust against various types of perturbations, but we still do not know the mechanism of robustness. In this paper, we find that there exist a number of feedback loops in a real biological network compared to randomly generated networks. Moreover, we investigate how the topological property affects network robustness. To this end, we properly define the notion of robustness based on a Boolean network model. Through extensive simulations, we show that the Boolean networks create a nearly constant number of fixed-point attractors, while they create a smaller number of limit-cycle attractors as they contain a larger number of feedback loops. In addition, we elucidate that a considerably large basin of a fixed-point attractor is generated in the networks with a large number of feedback loops. All these results imply that the existence of a large number of feedback loops in biological networks can be a critical factor for their robust behaviors.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.237-244
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• 1994

We investigated the qualitive and quantitative properties in EEG signal which responds to auditory stimulus with increaing the sound-cutting frequency from 2 Hz to 20 Hz by 2 Hz step units, by chaotic dynamics. To bigin with, general chaotic properties such as fractal mechanism, 1 If frequency spectrum and positive Lyapunov exponent are discussed in EEG signal. For evoked potential with given auditory stimulus, the route to chaos by bifurcation diagram and the changes in geometrical property of Poincare sections of 2-dimensional psedophase space is observed. For that containing spontaneous potential, seen as the random background signal, the chaotic attractors in 3-dimensional phase space are found containing the same infomation as the above mentioned evoked potential. Finally the chinges of Lyapunov exponent by various sound-cutting frequencies of stimulus and by the various spatial positions (occipital region) in a brain surface to be measured, are illustrated meaningfully.