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Asymmetric Gaussian and its application to pattern recognition. (English) Zbl 1073.68765
Caelli, Terry (ed.) et al., Structural, syntactic, and statistical pattern recognition. Joint IAPR international workshops, SSPR 2002 and SPR 2002, Windsor, Ontario, Canada, August 6–9, 2002. Proceedings. Berlin: Springer (ISBN 3-540-44011-9). Lect. Notes Comput. Sci. 2396, 405-413 (2002).
Summary: In this paper, we propose a new probability model, ‘asymmetric Gaussian (AG),’ which can capture spatially asymmetric distributions. It is also extended to mixture of AGs. The values of its parameters can be determined by Expectation-Conditional Maximization algorithm. We apply the AGs to a pattern classification problem and show that the AGs outperform Gaussian models.
For the entire collection see [Zbl 0993.00045].

MSC:
68T10 Pattern recognition, speech recognition
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