Ring of map -based neural oscillators: From order to chaos and back

被引：13
作者：
Bashkirtseva, Irina A. [1 ]
Ryashko, Lev B. [1 ]
Pisarchik, Alexander N. [2 ,3 ]
机构：
[1] Ural Fed Univ, Inst Math & Comp Sci, Ekaterinburg 620000, Russia
[2] Tech Univ Madrid, Ctr Biomed Technol, Madrid 28223, Spain
[3] Innopolis Univ, Ctr Technol Robot & Mechatron Component, Innopolis 450200, Russia
来源：
CHAOS SOLITONS & FRACTALS | 2020年 / 136卷
基金：
俄罗斯科学基金会;
关键词：
LYAPUNOV EXPONENTS; SYNCHRONIZATION; DYNAMICS; NOISE; NEURONS; MODEL; STABILITY; NETWORKS; DISEASE; MEMORY;
D O I：
10.1016/j.chaos.2020.109830
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
We study transitions from regular to chaotic dynamics and back of a ring of three map-based neurons with parameter mismatch. First, we consider the case when each neuron being isolated is in a stable equilibrium and show that an increase in the coupling strength can lead to chaotic dynamics following a quasiperiodic behavior. Then, we consider the case when the uncoupled neurons are in a chaotic state and demonstrate the route from chaos to periodicity as the coupling strength is increased. We show that this interesting effect results from lag synchronization of the coupled neural oscillators. The system stability is characterized by the largest Lyapunov exponents in the space of the coupling strength and parameter mismatch, while lag synchronization is measured using the similarity function. © 2020
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页数：9
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