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SUMMARY This paper is concerned with estimating the dimension of an attractor. The Grassberger–Procaccia procedure for estimating the correlation dimension is reviewed, and some alternative estimators considered. A particularly important problem is to estimate dimension in the presence of noise in the data. In pursuit of this, a modification of the Grassberger–Procaccia procedure is proposed, and illustrated on both artificial and real data sets.
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Richard L. Smith (1992) studied this question.
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