Liberati D, Cerutti S, Di Ponzio E, Ventimiglia V, Zaninelli L. The implementation of an autoregressive model with exogenous input in a single sweep visual evoked potential analysis.
J Biomed Eng 1989;
11:285-92. [PMID:
2666748 DOI:
10.1016/0141-5425(89)90061-7]
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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.
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