https://doi.org/10.1140/epjp/s13360-024-04950-5
Regular Article
Mitigation of extreme events in an excitable system
1
Department of Nonlinear Dynamics, Bharathidasan University, 620024, Tiruchirappalli, Tamil Nadu, India
2
Physics and Applied Mathematics Unit, Indian Statistical Institute, 700108, Kolkata, West Bengal, India
3
Department of Physics, Nehru Memorial College (Autonomous), 621007, Tiruchirappalli, Tamil Nadu, India
Received:
2
November
2023
Accepted:
27
January
2024
Published online:
1
March
2024
Formulating mitigation strategies is one of the main aspect in the dynamical study of extreme events. Apart from the effective control, easy implementation of the devised tool should also be given importance. In this work, we analyze the mitigation of extreme events in a coupled FitzHugh–Nagumo (FHN) neuron model utilizing an easily implementable constant bias analogous to a constant DC stimulant. We report the route through which the extreme events gets mitigated in Two, Three and 
coupled FHN systems. In all the three cases, extreme events in the observable 
gets suppressed. We confirm our results with the probability distribution function of peaks, 
plot and probability plots. Here is a measure of number of standard deviations that crosses the average amplitude corresponding to 
. Interestingly, we found that constant bias suppresses the extreme events without changing the collective frequency of the system.
Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
