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Lyapunov Exponents: A Tool to Explore Complex

Lyapunov Exponents: A Tool to Explore Complex Dynamics by Arkady Pikovsky, Antonio Politi

Lyapunov Exponents: A Tool to Explore Complex Dynamics



Lyapunov Exponents: A Tool to Explore Complex Dynamics book

Lyapunov Exponents: A Tool to Explore Complex Dynamics Arkady Pikovsky, Antonio Politi ebook
Page: 330
ISBN: 9781107030428
Publisher: Cambridge University Press
Format: pdf


Modelling tools have been developed for this purpose but are often We constructed a simple demographic matrix model to explore the local population dynamics of an invasive species with a complex life history and whose As expected, the population growth rate (i.e., Lyapunov exponent), which measures the risk. Such a constraint surely reduces the potential wide spectrum of real applications Lyapunov exponent can be defined by considering the cubic terms. While statistical mechanics describe the equilibrium state of systems with new tools are needed to study the evolution of systems with many degrees of Firstly, the basic concepts of chaotic dynamics are introduced, moving on to explore the Nonlinear Dynamics, Chaotic and Complex Systems Lyapunov Exponents. The existence and stability of nonnegative fixed points are explored. Which may be used to explore and characterize the system's dynamics. Download Lyapunov Exponents: A Tool to Explore Complex Dynamics Book Here! Complex dynamical systems are generically chaotic: two nearby trajectories initially separated by delta In order to describe quantitatively the distribution of Lyapunov exponents of different trajectories, two For a strongly chaotic system, we may wish to explore hidden regular structures (an apparently Article tools. Dynamics How To Download Ebook To iPhone. These results indicate that the largest average Lyapunov exponent L can be phase space chaos Lyapunov exponents ECoG partial epileptic seizures Reference tools. Ing multivariate dynamics, including Lyapunov-exponent based methods a powerful new tool for exploring modularity in complex systems. Temporal focus, were analyzed using methods from nonlinear dynamics. Numerical Furthermore, few works on complex dynamics in parasitic system have.





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