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ICPR
2000
IEEE

Rough Histograms for Robust Statistics

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Rough Histograms for Robust Statistics
Applied statistics are widely used in pattern recognition and other computing applications tofind the most likely value of a parameter. The use of classical empirical statistics is based upon assumption about normality of underhing density distribution of data. Whenthe data is corrupted by contaminated noise, then classical tools are usually not robust enough and the estimation of the mode is biased. In this article, we propose to estimate the main mode of a distribution by means of a rough histogram and we show that this estimation is robust to contamination.
Olivier Strauss, Frederic Comby, Marie-José
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where ICPR
Authors Olivier Strauss, Frederic Comby, Marie-José Aldon
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