False Asymptotic Instability Behavior at Iterated Functions with Lyapunov Stability in Nonlinear Time Series

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Abstract

Empirically defining some constant probabilistic orbits of iterated high-order functions, the stability of these functions in possible entangled interaction dynamics of the environment through its orbit’s connectivity (open sets) provides the formation of an exponential dynamic fixed point as a metric space (topological property) between both iterated functions for short time lengths. However, the presence of a dynamic fixed point can identify a convergence at iterations for larger time lengths (asymptotic stability in Lyapunov sense). Qualitative (QDE) results show that the average distance between the discontinuous function to the fixed point of the continuous function (for all possible solutions), might express fluctuations of on time lengths (instability effect). This feature can reveal the false empirical asymptotic instability behavior between the given domains due to time lengths observation and empirical constraints within a well-defined Lyapunov stability.

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Telles, C. R. (2020). False Asymptotic Instability Behavior at Iterated Functions with Lyapunov Stability in Nonlinear Time Series. In Advances in Intelligent Systems and Computing (Vol. 1230 AISC, pp. 673–693). Springer. https://doi.org/10.1007/978-3-030-52243-8_51

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