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Estimation of evoked potentials using total least squares prony technique. 1998

T Akkin, and S Saliu
Department of Electrical and Electronics Engineering, Cukurova University, Adana, Turkey. takkin@pamuk.cu.edu.tr

The authors investigate the applicability of Prony modelling to the estimation of evoked potentials. Four types of total least squares (TLS) model are considered and their optimal parameters are defined based on ten visual averaged EPs. Simulations with various signal and noise characteristics show that the TLS-Prony estimation is superior to averaging for two of the models, namely the unconstrained and the stable models. Application of the TLS-Prony estimator as a post-processor to moderate averaging allows a reduction in the number of responses averaged, or equivalently of recording time, by a factor of two.

UI MeSH Term Description Entries
D005074 Evoked Potentials, Visual The electric response evoked in the cerebral cortex by visual stimulation or stimulation of the visual pathways. Visual Evoked Response,Evoked Potential, Visual,Evoked Response, Visual,Evoked Responses, Visual,Potential, Visual Evoked,Potentials, Visual Evoked,Response, Visual Evoked,Responses, Visual Evoked,Visual Evoked Potential,Visual Evoked Potentials,Visual Evoked Responses
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012815 Signal Processing, Computer-Assisted Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity. Digital Signal Processing,Signal Interpretation, Computer-Assisted,Signal Processing, Digital,Computer-Assisted Signal Interpretation,Computer-Assisted Signal Interpretations,Computer-Assisted Signal Processing,Interpretation, Computer-Assisted Signal,Interpretations, Computer-Assisted Signal,Signal Interpretation, Computer Assisted,Signal Interpretations, Computer-Assisted,Signal Processing, Computer Assisted
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016018 Least-Squares Analysis A principle of estimation in which the estimates of a set of parameters in a statistical model are those quantities minimizing the sum of squared differences between the observed values of a dependent variable and the values predicted by the model. Rietveld Refinement,Analysis, Least-Squares,Least Squares,Analyses, Least-Squares,Analysis, Least Squares,Least Squares Analysis,Least-Squares Analyses,Refinement, Rietveld

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