We present an adaptive observer which asymptotically reconstructs the parameters and states of a model of interconnected cortical columns. Our study is motivated by the fact that the considered model is able to realistically reproduce patterns seen on (intracranial) electroencephalograms (EEG) by varying its parameters. Therefore, by estimating its parameters and states, we could gain a better understanding of the mechanisms underlying neurological phenomena such as seizures, which might lead to the prediction of the onsets of epileptic seizures. Simulations are performed to illustrate our results.
|Number of pages||6|
|Journal||Proceedings of the IEEE Conference on Decision and Control|
|Publication status||Published - 1 Dec 2012|
|Event||IEEE Conference on Decision and Control 2012 - Grand Wailea, Maui, United States of America|
Duration: 10 Dec 2012 → 13 Dec 2012
Conference number: 51st