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Proceedings Paper

Model-independent technique for determining the embedding dimension
Author(s): Daniel T. Kaplan
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Paper Abstract

The method of lag-embedding, common in the analysis of signals in the context of nonlinear dynamics, requires the selection of an embedding dimension. This embedding dimension is analogous to the model order in a linear prediction model, but the order of a linear prediction model is of little use in characterizing chaotic signals or in indicating an appropriate embedding dimension for nonlinear analysis. Nonlinear prediction models, however, have been successfully used for this purpose. Here, we describe a technique for selecting an appropriate embedding dimension that is motivated by nonlinear prediction, but does not require the specification of the form of a prediction model.

Paper Details

Date Published: 18 November 1993
PDF: 5 pages
Proc. SPIE 2038, Chaos in Communications, (18 November 1993); doi: 10.1117/12.162676
Show Author Affiliations
Daniel T. Kaplan, McGill Univ. (Canada)


Published in SPIE Proceedings Vol. 2038:
Chaos in Communications
Louis M. Pecora, Editor(s)

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