We study intrinsic properties of attractor in Boolean dynamics of complex networks with scale-free topology, comparing with those of the so-called Kauffman's random Boolean networks. We numerically study both frozen and relevant nodes in each attractor in the dynamics of relatively small networks (20<or=N<or=200). We investigate numerically robustness of an attractor to a perturbation. An attra...

It is shown that the incorporation of linear sink/source terms in three-wave resonance interaction model results time dependence wave amplitudes, which could exhibit properties a strange attractor. This finding demonstrates transition to turbulent dynamics waves be related not only coupling triads but also establishing attractor-like within individual triads.

25 On the genetic "memory" of chaotic attractor of the barotropic ocean model. Abstract. The structure of the attractor of the barotropic ocean model is studied in this paper. This structure is partially explained by the sequence of bifurcation the system is subjected by variations of the leading parameters. The principal feature of the studied system is the existence of two "almost invariant" ...

The outcomes of intertemporal choices indicate that people discount rewards by their delay. These outcomes are well described by discounting functions. However, to fully understand the decision process one needs models describing how the process of decision-making unfolds dynamically over time. Here, we validate a recently published attractor model that extends discounting functions through a d...

A very simple model of two reciprocally connected attractor neural networks is studied analytically in situations similar to those encountered in delay match-to-sample tasks with intervening stimuli and in tasks of memory guided attention. The model qualitatively reproduces many of the experimental data on these types of tasks and provides a framework for the understanding of the experimental o...

The accuracy with which cancer phenotypes can be predicted by selecting and combining molecular features is compromised by the large number of potential features available. In an effort to design a robust prognostic model to predict breast cancer survival, we hypothesized that signatures consisting of genes that are coexpressed in multiple cancer types should correspond to molecular events that...

different discrete models of population dynamics of certain insects have been investigated under various feasible conditions within the framework of nonlinear dynamics. evolutionary phenomena are discussed through bifurcation analysis leading to chaos. some tools of nonlinear dynamics, such as lyapunov characteristic exponents (lce), lyapunov numbers, correlation dimension, etc. are calculated ...

In this paper it is shown how to model times series by using random iterated neural networks with place-dependent probabilities. The model assumes that the time series comes from a dynamical system which has a compact global attractor and a physical probability measure supported on the attractor. Also, an evolutionary algorithm is used to train a random iterated neural network that models a nan...

A new 3D autonomous dynamical system proposed by Dequan Li [Physics Letters A, 372, 387, 2008.] produces a chaotic attractor whose global topological properties are unusual. The attractor has a rotation symmetry and only a single real fixed point for the parameters used in his study. The symmetric, complex pair of fixed points cannot be ignored: they play a major role in organizing the motion o...

In this paper we introduce a new chaotic system and its corresponding circuit. This system has a special property of having a hidden attractor. Systems with hidden attractors are newly introduced and barely investigated. Conventional methods for parameter estimation in models of these systems have some limitations caused by sensitivity to initial conditions. We use a geometry based cost functio...