Iterative learning control of synchronization of Hodgkin-Huxley neurons.

Because of the uncertainties of neuron model and its parameters, some control methods become cumbersome. Iterative learning control (ILC) is independent of the exact system model, therefore is suitable for control of neural network synchronization. This paper proposed PI-type iterative learning control algorithm for synchronization control of Hodgkin-Huxley (HH) neurons. Simulation of synchronization control of master and slave neurons in four cases shows that, when the control is implemented, the dynamic behavior of the controlled slave neuron can rapidly synchronize with that of the master one. The results confirm the feasibility and effectiveness of this control algorithm. [ABSTRACT FROM AUTHOR]