title: The implementation of an autoregressive model with exogenous input in a single sweep visual evoked potential analysis.
abstract: Based on a model of signal-noise interaction, we present a method for single-sweep analysis of Visual Evoked Potentials. The EEG is represented as an autoregressive process and the single-sweep VEP as a filtered version of a reference signal taken as the running average of 20 consecutive sweeps. The algorithm for model identification and filtering is an ARX (AutoRegressive with eXogenous input) which provides a fast and efficient solution by means of a least squares approach. The choice of reference signal, as well as the complexity of the model, is also discussed. A further advantage of this approach is parameter reduction: all the single-sweep information is contained in 18 model coefficients and the reference signal.
authors.affiliation: CNR, Centro Teoria dei Sistemi, Milano, Italy.
authors.forename: D
authors.initials: D
authors.lastname: Liberati
authors.forename: S
authors.initials: S
authors.lastname: Cerutti
authors.forename: E
authors.initials: E
authors.lastname: Di Ponzio
authors.forename: V
authors.initials: V
authors.lastname: Ventimiglia
authors.forename: L
authors.initials: L
authors.lastname: Zaninelli
mesh_terms: D005074:Evoked Potentials, Visual; D006801:Humans; D008959:Models, Neurological