Search results for "Nonlinear Sciences::Chaotic Dynamics"

showing 10 items of 131 documents

Looking More Closely at the Rabinovich-Fabrikant System

2016

Recently, we looked more closely into the Rabinovich–Fabrikant system, after a decade of study [Danca & Chen, 2004], discovering some new characteristics such as cycling chaos, transient chaos, chaotic hidden attractors and a new kind of saddle-like attractor. In addition to extensive and accurate numerical analysis, on the assumptive existence of heteroclinic orbits, we provide a few of their approximations.

Control of chaosheteroclinic orbitLIL numerical methodApplied Mathematicsta111Chaotictransient chaos01 natural sciencesRabinovich-Fabrikant system010305 fluids & plasmasNonlinear Sciences::Chaotic DynamicsClassical mechanicsModeling and Simulation0103 physical sciencesAttractorHeteroclinic orbitStatistical physicscycling chaos010301 acousticsEngineering (miscellaneous)MathematicsInternational Journal of Bifurcation and Chaos
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The pianigiani-yorke measure for topological markov chains

1997

We prove the existence of a Pianigiani-Yorke measure for a Markovian factor of a topological Markov chain. This measure induces a Gibbs measure in the limit set. The proof uses the contraction properties of the Ruelle-Perron-Frobenius operator.

Discrete mathematicsMathematics::Dynamical SystemsMarkov chain mixing timeMarkov chainGeneral MathematicsMarkov processPartition function (mathematics)TopologyHarris chainNonlinear Sciences::Chaotic Dynamicssymbols.namesakeBalance equationsymbolsExamples of Markov chainsGibbs measureMathematicsIsrael Journal of Mathematics
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Construction of chaotic dynamical system

2010

The first‐order difference equation xn+ 1 = f(xn ), n = 0,1,…, where f: R → R, is referred as an one‐dimensional discrete dynamical system. If function f is a chaotic mapping, then we talk about chaotic dynamical system. Models with chaotic mappings are not predictable in long‐term. In this paper we consider family of chaotic mappings in symbol space S 2. We use the idea of topological semi‐conjugacy and so we can construct a family of mappings in the unit segment such that it is chaotic. First published online: 09 Jun 2011

Discrete mathematicsPure mathematicsincreasing mappingDifferential equationChaoticinfinite symbol spaceBinary numberFunction (mathematics)Space (mathematics)Nonlinear Sciences::Chaotic Dynamicstopological semi‐conjugacyModeling and SimulationQA1-939Orbit (dynamics)chaotic mappingbinary expansionUnit (ring theory)MathematicsAnalysisMathematicsCoupled map latticeMathematical Modelling and Analysis
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A wavelet-based tool for studying non-periodicity

2010

This paper presents a new numerical approach to the study of non-periodicity in signals, which can complement the maximal Lyapunov exponent method for determining chaos transitions of a given dynamical system. The proposed technique is based on the continuous wavelet transform and the wavelet multiresolution analysis. A new parameter, the \textit{scale index}, is introduced and interpreted as a measure of the degree of the signal's non-periodicity. This methodology is successfully applied to three classical dynamical systems: the Bonhoeffer-van der Pol oscillator, the logistic map, and the Henon map.

Dynamical systems theoryFOS: Physical sciencesLyapunov exponentDynamical Systems (math.DS)37D99 42C40WaveletsDynamical systemMeasure (mathematics)symbols.namesakeWaveletModelling and SimulationFOS: MathematicsApplied mathematicsMathematics - Dynamical SystemsContinuous wavelet transformMathematicsMathematical analysisNonlinear Sciences - Chaotic DynamicsNon-periodicityHénon mapNonlinear Sciences::Chaotic DynamicsComputational MathematicsComputational Theory and MathematicsModeling and SimulationsymbolsLogistic mapChaotic Dynamics (nlin.CD)Chaotic dynamical systems
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Random Walk in a N-cube Without Hamiltonian Cycle to Chaotic Pseudorandom Number Generation: Theoretical and Practical Considerations

2017

Designing a pseudorandom number generator (PRNG) is a difficult and complex task. Many recent works have considered chaotic functions as the basis of built PRNGs: the quality of the output would indeed be an obvious consequence of some chaos properties. However, there is no direct reasoning that goes from chaotic functions to uniform distribution of the output. Moreover, embedding such kind of functions into a PRNG does not necessarily allow to get a chaotic output, which could be required for simulating some chaotic behaviors. In a previous work, some of the authors have proposed the idea of walking into a $\mathsf{N}$-cube where a balanced Hamiltonian cycle has been removed as the basis o…

FOS: Computer and information sciencesUniform distribution (continuous)Computer Science - Cryptography and SecurityComputer scienceHamiltonian CycleChaoticPseudorandom Numbers GeneratorFOS: Physical sciences02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]01 natural sciencesUpper and lower bounds[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computingsymbols.namesake[INFO.INFO-MC]Computer Science [cs]/Mobile Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringApplied mathematics[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]0101 mathematicsEngineering (miscellaneous)Pseudorandom number generatorChaotic IterationsBasis (linear algebra)Applied Mathematics020208 electrical & electronic engineering010102 general mathematicsRandom walkNonlinear Sciences - Chaotic DynamicsHamiltonian path[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationNonlinear Sciences::Chaotic Dynamics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Modeling and SimulationRandom Walk[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]symbolsPseudo random number generator[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Chaotic Dynamics (nlin.CD)[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Cryptography and Security (cs.CR)
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Chaotic behavior in deformable models: the double-well doubly periodic oscillators

2001

Abstract The motion of a particle in a one-dimensional perturbed double-well doubly periodic potential is investigated analytically and numerically. A simple physical model for calculating analytically the Melnikov function is proposed. The onset of chaos is studied through an analysis of the phase space, a construction of the bifurcation diagram and a computation of the Lyapunov exponent. The parameter regions of chaotic behavior predicted by the theoretical analysis agree very well with numerical simulations.

General MathematicsApplied MathematicsComputationMathematical analysisChaoticGeneral Physics and AstronomyMotion (geometry)Statistical and Nonlinear PhysicsLyapunov exponentBifurcation diagramNonlinear Sciences::Chaotic Dynamicssymbols.namesakeClassical mechanicsSimple (abstract algebra)Phase spacesymbolsParticleMathematicsChaos, Solitons & Fractals
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Chaotic behaviour in deformable models: the asymmetric doubly periodic oscillators

2002

Abstract The motion of a particle in a one-dimensional perturbed asymmetric doubly periodic (ASDP) potential is investigated analytically and numerically. A simple physical model for calculating analytically the Melnikov function is proposed. The onset of chaos is studied through an analysis of the phase space, a construction of the bifurcation diagram and a computation of the Lyapunov exponent. Theory predicts the regions of chaotic behaviour of orbits in a good agreement with computer calculations.

General MathematicsApplied MathematicsComputationMathematical analysisChaoticGeneral Physics and AstronomyMotion (geometry)Statistical and Nonlinear PhysicsLyapunov exponentBifurcation diagramNonlinear Sciences::Chaotic Dynamicssymbols.namesakeSimple (abstract algebra)Phase spacesymbolsMelnikov methodMathematicsChaos, Solitons & Fractals
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Coupled Discrete Fractional-Order Logistic Maps

2021

This paper studies a system of coupled discrete fractional-order logistic maps, modeled by Caputo’s delta fractional difference, regarding its numerical integration and chaotic dynamics. Some interesting new dynamical properties and unusual phenomena from this coupled chaotic-map system are revealed. Moreover, the coexistence of attractors, a necessary ingredient of the existence of hidden attractors, is proved and analyzed.

General Mathematicscaputo delta fractional differenceChaoticattraktoritstabilityStability (probability)fractional-order difference equationNumerical integrationNonlinear Sciences::Chaotic DynamicsAttractorQA1-939Computer Science (miscellaneous)Applied mathematicsOrder (group theory)dynaamiset systeemitEngineering (miscellaneous)Mathematicsdiscrete fractional-order systemhidden attractorMathematicsMathematics
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Noncommutative space and the low-energy physics of quasicrystals

2008

We prove that the effective low-energy, nonlinear Schroedinger equation for a particle in the presence of a quasiperiodic potential is the potential-free, nonlinear Schroedinger equation on noncommutative space. Thus quasiperiodicity of the potential can be traded for space noncommutativity when describing the envelope wave of the initial quasiperiodic wave.

High Energy Physics - TheoryPhysicsNuclear and High Energy PhysicsQuasicrystalFOS: Physical sciencesAstronomy and AstrophysicsMathematical Physics (math-ph)Space (mathematics)Noncommutative geometryAtomic and Molecular Physics and OpticsNonlinear Sciences::Chaotic DynamicsQuasiperiodicitysymbols.namesakeLow energyHigh Energy Physics - Theory (hep-th)Quasiperiodic functionsymbolsNonlinear Schrödinger equationMathematical PhysicsMathematical physicsEnvelope (waves)
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Modified post-bifurcation dynamics and routes to chaos from double-Hopf bifurcations in a hyperchaotic system

2012

In order to understand the onset of hyperchaotic behavior recently observed in many systems, we study bifurcations in the modified Chen system leading from simple dynamics into chaotic regimes. In particular, we demonstrate that the existence of only one fixed point of the system in all regions of parameter space implies that this simple point attractor may only be destabilized via a Hopf or double Hopf bifurcation as system parameters are varied. Saddle-node, transcritical and pitchfork bifurcations are precluded. The normal form immediately following double Hopf bifurcations is constructed analytically by the method of multiple scales. Analysis of this generalized double Hopf normal form …

Hopf bifurcationApplied MathematicsMechanical EngineeringMathematical analysisAerospace EngineeringOcean EngineeringContext (language use)Parameter spaceBiological applications of bifurcation theoryNonlinear Sciences::Chaotic Dynamicssymbols.namesakePitchfork bifurcationControl and Systems EngineeringControl theoryQuasiperiodic functionAttractorsymbolsElectrical and Electronic EngineeringDouble-Hopf bifurcations – Normal forms – Modified post-bifurcation dynamicsSettore MAT/07 - Fisica MatematicaNonlinear Sciences::Pattern Formation and SolitonsBifurcationMathematicsNonlinear Dynamics
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