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Are the dimensions of a set and its image equal under typicalsmooth functions?

Published online by Cambridge University Press:  02 April 2001

TIMOTHY D. SAUER
Affiliation:
Department of Mathematical Sciences, George Mason University, Fairfax, VA 22030, USA
JAMES A. YORKE
Affiliation:
Institute of Physical Science and Technology, University of Maryland, College Park, MD 20742, USA
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Abstract

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We examine the question whether the dimension $D$ of a setor probability measure is the same as the dimension of itsimage under a typical smooth function, if the range spaceis at least $D$-dimensional. If $\mu$ is a Borelprobability measure of bounded support in ${\Bbb R}^n$with correlation dimension $D$, and if $m\geq D$, thenunder almost every continuously differentiable function(‘almost every’ in the sense of prevalence) from ${\BbbR}^n$ to ${\Bbb R}^m$, the correlation dimension of theimage of $\mu$ is also $D$. If $\mu$ is the invariantmeasure of a dynamical system, the same is true for almostevery delay coordinate map. That is, if $m\geq D$, then$m$ time delays are sufficient to find the correlationdimension using a typical measurement function. Further,it is shown that finite impulse response (FIR) filters donot change the correlation dimension. Analogous theoremshold for Hausdorff, pointwise, and information dimensions.We show by example that the conclusion fails forbox-counting dimension.

Information

Type
Research Article
Copyright
© 1997 Cambridge University Press