Peculiarities of coherence resonance in neural maps under Lévy noise
E. Rybalova1, A. Ryabov1, S. Muni2, G. Strelkova1;
1. Institute of Physics, Saratov State University, 83 Astrakhanskaya Street, Saratov, 410012, Russia
2. School of Digital Sciences, Digital University Kerala, Thiruvananthapuram, 695317, India
Abstract
This study investigates coherent resonance in map-based neural models in the presence of a Lévy noise source. The influence of various Lévy noise parameters on several neural maps is analyzed numerically. The investigation utilizes the Rulkov map, the Chialvo map, and the Courbage–Nekorkin–Vdovin map in the excitable mode. The results demonstrate that the coherence of oscillations caused by Lévy noise decreases as the stability parameter decreases. Additionally, changing the skewness parameter can either reduce or increase the coherence. However, there are differences in how coherent resonance is manifested. The Rulkov map and the Chialvo map achieve the minimum value of the normalized standard deviation of the interstitial intervals with negative values of the skewness parameter, while the Courbage–Nekorkin–Vdovin map achieves this with positive values of the skewness parameter.
This work was supported by the Russian Science Foundation (Project No. 20-12-00119,
https://rscf.ru/en/project/20-12-00119/).
Speaker
Aleksey Ryabov
Saratov State University
Russia
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