Nonlinear prediction of brain electrical activity in epilepsy with a Volterra RLS algorithm
Christian Niederhofer, Shaolong Suna, Ronald Tetzlaff · 2003
Approximately 0.3% of the world's population is suffering from a focal epilepsy. In this paper the bioelectrical activity of the human brain in epilepsy will be analyzed with Volterra-systems (VS), whereas the kernels of different orders will be determined by using an RLS (recursive least squares) method of reduced computation complexity. The prediction gain for data segments obtained in presurgical evaluations will be given and criteria for a detection of distinct changes of the prediction coefficients will be proposed.