Chaotic Synchronization of Two Electrical Coupled Neurons with Unknown Parameters Based on Adaptive Control

Chaotic synchronization of two electrical coupled FitzHugh–Nagumo (FHN) neurons with unknown parameters via adaptive control is investigated. Based on the Lyapunov stability theory, an adaptive controller and a parameter update law are designed, which can achieve the synchronization of the two gap junction coupled FHN neurons when the individual neuron is chaotic, without considering the coupling strength. Moreover, the unknown parameters are identified successfully and the controller is robust to the random noise. The numerical simulation results confirm the effectiveness of the designed controller.