Murtagh, Fionn (2004) Thinking ultrametrically In: Classification, Clustering, and Data Mining Applications. Springer-Verlag, Berlin.
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The triangular inequality is a defining property of a metric space, while the stronger ultrametric inequality is a defining property of an ultrametric space. Ultrametric distance is defined from p-adic valuation. It is known that ultrametricity is a natural property of spaces that are sparse. Here we look at the quantification of ultrametricity. We also look at data compression based on a new ultrametric wavelet transform. We conclude with computational implications of prevalent and perhaps ubiquitous ultrametricity.
This is a Published version This version's date is: 2004 This item is not peer reviewed
https://repository.royalholloway.ac.uk/items/90d87408-fdf2-5b0c-23a8-5d7c21d00c5a/1/
Deposited by () on 23-Dec-2009 in Royal Holloway Research Online.Last modified on 23-Dec-2009