Various Dynamics of Amplitude Regulation Within a Class of 3D Rulkov Neurons

Chaotic behavior can be improved through specific types of nonlinear feedback, thereby offering profound insights into chaos control. In this work, a class of nonlinear functions is utilized as feedback to explore the various dynamics of amplitude regulation in the modified 3D Rulkov neurons, thereby changing its brain-like firing patterns. Three different functions are embedded in Rulkov neurons for the outcome of complex dynamics, including the amplitude and frequency control of firing oscillation. Specifically, the pumping effect from a neuron parameter is analyzed, where the energy and amplitude of the firing are almost linearly rescaled by the input acting as a pivotal element for enhancing the transmission of neural signals. Furthermore, when the nonlinear feedback is obtained from a periodic function, coexisting double-scroll phase orbits induced by the initially-controlled offset boosting are arranged in phase space with the same shape and different amplitude. Finally, the digital circuit implemented by CH32 is carried out to verify complex firings. The Pseudo-Random Number Generator is employed as the technology to show the complexity of chaotic firing.