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Updated: Oct 3, 2026

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
Published on: July 1, 2015
Embedding of multidimensional time-dependent observations
J P Barnard1, C Aldrich, M Gerber
1Department of Chemical Engineering, University of Stellenbosch, Private Bag X1, Matieland, Stellenbosch, 7602 South Africa. jsteyl@ing.sun.ac.za
Abstract:
A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.
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