Abstract
We propose to control the orbits of the two-dimensional Rulkov model affected by
bounded noise. For the correct parameter choice the phase space presents two chaotic
regions separated by a transient chaotic region in between. One of the chaotic regions is
the responsible to give birth to the neuronal bursting regime. Normally, an orbit in this
chaotic region cannot pass through the transient chaotic one and reach the other chaotic
region. As a consequence the burstings are short in time. Here, we propose a control
technique to connect both chaotic regions and allow the neuron to exhibit very long
burstings. This control method defines a region Q covering the transient chaotic region
where it is possible to find an advantageous set S ⊂ Q through which the orbits can be
driven with a minimal control. In addition we show how the set S changes depending
on the noise intensity affecting the map, and how the set S can be used in different
scenarios of control.
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Elsevier
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This work has been supported by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERDF, EU) under Project No. PID2019-105554GB-I00 (MCIN/AEI/10.13039/501100011033).
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Jennifer López, Mattia Coccolo, Rubén Capeáns, Miguel A.F. Sanjuán, Controlling the bursting size in the two-dimensional Rulkov model, Communications in Nonlinear Science and Numerical Simulation, Volume 120, 2023, 107184, ISSN 1007-5704, https://doi.org/10.1016/j.cnsns.2023.107184
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