Synchronization of a Network Composed of Stochastic Hindmarsh-Rose Neurons

An algorithm for synchronization of a network composed of interconnected Hindmarsh-Rose neurons is presented. Delays are present in the interconnections of the neurons. Noise is added to the controlled input of the neurons. The synchronization algorithm is designed using convex optimization and is formulated by means of linear matrix inequalities via the stochastic version of the Razumikhin functional. The recovery and the adaptation variables are also synchronized; this is demonstrated with the help of the minimum-phase property of the Hindmarsh-Rose neuron. The results are illustrated by an example.

Automated summary

An algorithm for synchronization of interconnected Hindmarsh-Rose neurons network is presented, incorporating delays and noise in the network. The synchronization algorithm utilizes convex optimization and linear matrix inequalities formulation, showing synchronized recovery and adaptation variables through the minimum-phase property of the Hindmarsh-Rose neuron. The results are demonstrated with an example.