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The Lyapunov largest exponent and Poincaré map of phase trajectories methods have been used with this purpose in mind.
Therefore, the dominant factor which determines the CAF scheme complexity will be the one with the largest exponent, thus the complexity of the method will be upper bounded by (mathcal {O} (|S_{n}|^{2})) operations.
However in practice, only the largest exponent is calculated as this dominates the trajectory divergence [ 21].
You can remove the largest exponent as a factor.
In the example, -x 4 + x 2 + x, the power of the first term is 4. Since you've arranged the polynomial to put the largest exponent first, that will be where you will find the largest term.
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Generally, the velocity and state feedback cases with a larger exponent can perform apparently better than the displacement feeedback case.
The decrement of the entransy dissipation rate tends to increase for the exponential temperature distribution case with a large exponent.
A larger exponent is related to a wider distribution of localized states in the tail of an exponential density of states and thus to higher disorder of the system.
If any, perform the mantissa shift and set the larger exponent as the tentative exponent of the result.
For "longer" waiting times, the distribution is dominated by the much larger exponent β∼3, a regime in which consecutive avalanches would be independent.
Similarly, the slightly larger exponent of −0.15 that relates specific brain metabolism to brain mass across larger mammalian samples [20] can be accounted for by an apparent scaling of neuronal density with brain mass raised to an exponent that varies depending on the choice of species.
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