A discrete dynamical system as a model of a neural network with generalized Hebbian synapses

We study the dynamical behavior of a discrete time dynamical system which can serve as a model of a learning process. We determine fixed points of this system and basins of attraction of attracting points. This system was studied by Fernanda Botelho and James J. Jamison in [A learning rule with generalized Hebbian synapses, J. Math. Anal. Appl. 273 (2002) 529-547] but authors used its continuous counterpart to describe basins of attraction.     

Two characteristics of planar intertwined basins of attraction

In this paper, we investigate the intertwined basins of attraction for planar dynamical systems. We prove that the intertwining property is preserved by topologically equivalent systems. Two necessary and sufficient conditions for a planar system having intertwined basins are given.     

Partially nearly riddled basins in systems with chaotic saddle

We show that chaotic attractors can have partially nearly riddled basins of attraction, i.e., basins which consist both of large open sets and a set in which small open sets which belong to the basins of different attractors are intermingled. We argue that such basins are robust for systems with the chaotic saddle located between at least two attractors and in the presence of noise cause the uncertainties similar to those implied by riddled basins.     

Selection of windows, attractors and self-similar patterns in a coupled map lattice

It is shown that a lattice of diffusively coupled logistic maps displays self-similar period-doubling cascades to chaos with all the known stages of pattern formation. The location of the self-similar patterns is determined. The basins of attraction yielding window structures, so far believed to be negligibly small, are shown to cover virtually all initial conditions given a certain maximum amplitude to the random initial conditions. As a consequence a means for selecting attractors in a CML is obtained. A new pattern selection regime at high nonlinearity is reported and the basins of attraction of some attractors of small lattices are investigated.     

Emergence of density dynamics by surface interpolation in elementary cellular automata

A classic problem in elementary cellular automata (ECAs) is the specification of numerical tools to represent and study their dynamical behaviour. Mean field theory and basins of attraction have been commonly used; however, although the first case gives the long term estimation of density, frequently it does not show an adequate approximation for the step-by-step temporal behaviour; mainly for non-trivial behaviour. In the second case, basins of attraction display a complete representation of the evolution of an ECA, but they are limited up to configurations of 32 cells; and for the same ECA, one can obtain tens of basins to analyse. This paper is devoted to represent the dynamics of density in ECAs for hundreds of cells using only two surfaces calculated by the nearest-neighbour interpolation. A diversity of surfaces emerges in this analysis. Consequently, we propose a surface and histogram based classification for periodic, chaotic and complex ECA.     

Dissipative relativistic standard map: Periodic attractors and basins of attraction

The dissipative relativistic standard map, introduced by Ciubotariu et al. [Ciubotariu C, Badelita L, Stancu V. Chaos in dissipative relativistic standard maps. Chaos, Solitons & Fractals 2002;13:1253–67.], is further studied numerically for small damping in the resonant case. We find that the attractors are all periodic; their basins of attraction have fractal boundaries and are closely interwoven. The number of attractors increases with decreasing damping. For a very small damping, there are thousands of periodic attractors, comprising mostly of the lowest-period attractors of period one or two; the basin of attraction of these lowest-period attractors is significantly larger compared to the basins of the higher-period attractors.     

Influence of the multiplicity of the roots on the basins of attraction of Newton’s method

In this work, we develop and implement two algorithms for plotting and computing the measure of the basins of attraction of rational maps defined on the Riemann sphere. These algorithms are based on the subdivisions of a cubical decomposition of a sphere and they have been made by using different computational environments. As an application, we study the basins of attraction of the fixed points of the rational functions obtained when Newton’s method is applied to a polynomial with two roots of multiplicities m and n. We focus our attention on the analysis of the influence of the multiplicities m and n on the measure of the two basins of attraction. As a consequence of the numerical results given in this work, we conclude that, if m > n, the probability that a point in the Riemann Sphere belongs to the basin of the root with multiplicity m is bigger than the other case. In addition, if n is fixed and m tends to infinity, the probability of reaching the root with multiplicity n tends to zero.     

Prey-predator systems with intertwined basins of attraction

In this article, we show the existence of intertwined basins of attraction for a class of prey-predator systems, which improves the extant results by deleting some crucial and hard testing conditions.     

Complex systems in drug research: I. The chemical levels

The hierarchy of chemical systems is examined. It is argued that an intermediate level of complexity, that of functional groups, exists between atoms and molecules. Molecular properties have an emergent nature, e.g., the “chameleonic behavior.” Aggregates of molecules and solutions also behave as complex systems. Emergent properties are particularly noteworthy in biological macromolecules and correspond to basins of attraction resulting from a complex interplay between intramolecular and intermolecular interactions.     

Newton's method on the complex exponential function

We show that when Newton's method is applied to the product of a polynomial and the exponential function in the complex plane, the basins of attraction of roots have finite area.

     

Investigating the Newton–Raphson basins of attraction in the restricted three-body problem with modified Newtonian gravity

The planar circular restricted three-body problem with modified Newtonian gravity is used in order to determine the Newton–Raphson basins of attraction associated with the equilibrium points. The evolution of the position of the five Lagrange points is monitored when the value of the power p of the gravitational potential of the second primary varies in predefined intervals. The regions on the configuration (x, y) plane occupied by the basins of attraction are revealed using the multivariate version of the Newton–Raphson iterative scheme. The correlations between the basins of convergence of the equilibrium points and the corresponding number of iterations needed for obtaining the desired accuracy are also illustrated. We conduct a thorough and systematic numerical investigation by demonstrating how the dynamical quantity p influences the shape as well as the geometry of the basins of attractions. Our results strongly suggest that the power p is indeed a very influential parameter in both cases of weaker or stronger Newtonian gravity.     

Stochastic control of attractor preference in a multistable system

When talking about the size of basins of attraction of coexisting states in a noisy multistable system, one can only refer to its probabilistic properties. In this context, the most probable size of basins of attraction of some coexisting states exhibits an obvious non-monotonous dependence on the noise amplitude, i.e., there exists a certain noise level for which the most probable basin’s size is larger than for other noise values, while the average size always decreases as the noise amplitude increases. Such a behavior is demonstrated through the study of the Hénon map with three coexisting attractors (period 1, period 3, and period 9). Since the position of the probabilistic extrema depends on the amplitude and frequency of external modulation applied to a system parameter, noise, periodic modulation and a combination of both provide an efficient control of attractor preference in a system with multiple coexisting states.     

Coexistence of domains of attraction of nonautonomous neural networks with time-varying delays

This paper presents new dynamical behavior, i.e., the coexistence of 2^N domains of attraction of N-dimensional nonautonomous neural networks with time-varying delays. By imposing some new assumptions on activation functions and system parameters, we construct 2^N invariant basins for neural system and derive some criteria on the boundedness and exponential attractivity for each invariant basin. Particularly, when neural system degenerates into periodic case, we not only attain the coexistence of 2^N periodic orbits in bounded invariant basins but also give their domains of attraction. Moreover, our results are suitable for autonomous neural systems. Our new results improve and generalize former ones. Finally, computer simulation is performed to illustrate the feasibility of our results.     

Optimized mean based second derivative-free families of Chebyshev–Halley type methods

In this paper, we present new interesting fourth-order optimal families of Chebyshev–Halley type methods free from second-order derivative. In terms of computational cost, eachmember of the families requires two functions and one first-order derivative evaluation per iteration, so that their efficiency indices are 1.587. It is found by way of illustration that the proposed methods are useful in high-precision computing environment. Moreover, it is also observed that larger basins of attraction belong to ourmethods although the othersmethods are slow and have darker basins while some of the methods are too sensitive upon the choice of the initial guess.     

Attraction probabilities in variable neighborhood search

Empirical evidence demonstrates that when the same local search operator is used, variable neighborhood search consistently outperforms random multistart local search on all types of combinatorial and global optimization problems tested. In this paper we suggest that this superiority in performance may be explained by the distribution of the attraction basins around a current solution as a function of the distance from the solution. We illustrate with a well-known instance of the multisource Weber problem that the “attraction probabilities” for finding better solutions can be orders of magnitude larger in neighborhoods that are close to the current solution. The paper also discusses the global convergence properties of both general methods in the context of attraction probabilities.     

Low-order resonances in weakly dissipative spin-orbit models

Second-order differential equations with small nonlinearity and weak dissipation, such as the spin-orbit model of celestial mechanics, are considered. Explicit conditions for the coexistence of periodic orbits and estimates on the measure of the basins of attraction of stable periodic orbits are discussed.     

关于局部随机吸引子若干性质的注记(英文)

In this note, we study some properties of local random pull-back attractors on compact metric spaces. We obtain some relations between attractors and their fundamental neighborhoods and basins of attraction. We also obtain some properties of omega-limit sets, as well as connectedness of random attractors. A simple deterministic example is given to illustrate some confusing problems.     

A family of multimodal dynamic maps

We introduce a family of multimodal logistic maps with a single parameter. The maps domain is partitioned in subdomains according to the maximal number of modals to be generated and each subdomain contains one logistic map. The number of members of a family is equal to the maximal number of modals. Bifurcation diagrams and basins of attraction of fixed points are constructed for the family of chaotic logistic maps.