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Nonlinear Dynamics and Complexity by Sarah de Nigris, Xavier Leoncini (auth.), Valentin

By Sarah de Nigris, Xavier Leoncini (auth.), Valentin Afraimovich, Albert C. J. Luo, Xilin Fu (eds.)

This crucial assortment provides contemporary advances in nonlinear dynamics together with analytical options, chaos in Hamiltonian structures, time-delay, uncertainty, and bio-network dynamics. Nonlinear Dynamics and Complexity equips readers to understand this more and more main-stream method of realizing complicated phenomena in nonlinear structures as they're tested in a extensive array of disciplines. The booklet enables a greater figuring out of the mechanisms and phenomena in nonlinear dynamics and develops the corresponding mathematical concept to use nonlinear layout to useful engineering.

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Extra resources for Nonlinear Dynamics and Complexity

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Actually the relaxation to the equilibrium is a delicate passage of our analysis: as explained in Sect. 2, the system can reach a stationary state in which the magnetization has a different value from the equilibrium and the length QS S of these states (QSS) increases with the system size as in Eq. (19). Therefore it is of crucial importance to check the evolution of the magnetization before taking the temporal mean, when these states 22 S. de Nigris and X. Leoncini can arise. Another point a bit technical that is worth to detail before proceeding is the numerical integration.

The estimate . k/ Ä (13) 2 2 is valid. k/ e . k/ e e=2 2e k 1 e=2 ! C1 1 as k ! C1. t/. Definition 12. t/. t/B, where B is a ball of unit radius. Definition 13 ([73]). A. V. Kuznetsov In the case (14) the terms upper singular exponent are also used [5]. Let 1 and 1 be the largest Lyapunov exponent and the largest characteristic exponent, respectively. Lemma 3. For the linear systems the largest characteristic exponent is equal to the largest Lyapunov exponent. Proof. t/ . C1 jxjD1 the relation 1 D 1.

L =N / 1 ; (29) where k is the spin degree of Eq. (4). 1 2 ˇ ˇ2 ˇOˇ l / ˇÂ l ˇ : (31) l Equation (30) derives from the fact that the eigenvectors of a circulant matrix of size N are the columns of the unitary discrete Fourier transform matrix of the same size. Using the linear waves representation and averaging over the phases in Eq. (31), we obtain: 30 S. de Nigris and X. 1 (32) Equation (32) is then an equation for an harmonic oscillator where the frequency is driven by adjacency matrix spectrum.

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