Universal Cellular Computing on the Edge of Chaos

In this work we present a special class of memristor Cellular Nonlinear/Nanoscale Networks (MCNN) operating on the edge of chaos. We study the dynamics of Gierer-Menhardt system for pattern formation in living cells. We determine three regions in the parameter set: locally active and stable, locally active and unstable and locally passive. Throughout extensive simulations we obtain non-uniform spatial-pattern generation of MCNN model in the edge of chaos domain. Applications in EEG signal generation are shown in order to predict the epileptic seizures.