Brain electrical activity in epilepsy: characterization of the spatio-temporal dynamics with cellular neural networks based on a correlation dimension analysis

We present a new approach for the analysis of the spatio-temporal dynamics of brain electrical activity in epilepsy with cellular neural networks (CNN). We have shown in recent investigations [1999] that the dimension D₂*(k, m) of brain electrical activity can be approximated by a function of CNN cell outputs. These results obtained with CNN, having non- steady-states, were sensitive to parameter deviations occurring in CNN hardware realizations. In this contribution we present an enhanced approximation method, which is based on a steady state determination showing an increased robustness and higher accuracy