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Title:Characterizing complex time-series from the scaling of prediction error
Author(s):Hinrichs, Brant Eric
Doctoral Committee Chair(s):Packard, Norman H.; Chialvo, Dante
Department / Program:Physics
Discipline:Physics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Biology, Biostatistics
Statistics
Physics, General
Abstract:This thesis concerns characterizing complex time series from the scaling of prediction error. We use the global modeling technique of radial basis function approximation to build models from a state-space reconstruction of a time series that otherwise appears complicated or random (i.e. aperiodic, irregular). Prediction error as a function of prediction horizon is obtained from the model using the direct method. The relationship between the underlying dynamics of the time series and the logarithmic scaling of prediction error as a function of prediction horizon is investigated. We use this relationship to characterize the dynamics of both a model chaotic system and physical data from the optic tectum of an attentive pigeon exhibiting the important phenomena of nonstationary neuronal oscillations in response to visual stimuli.
Issue Date:1994
Type:Text
Language:English
URI:http://hdl.handle.net/2142/22722
Rights Information:Copyright 1994 Hinrichs, Brant Eric
Date Available in IDEALS:2011-05-07
Identifier in Online Catalog:AAI9512394
OCLC Identifier:(UMI)AAI9512394


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