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6 April 1995 Feature extraction using self-organizing networks
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Abstract
Self-organizing networks are used to extract kinematical features and to study correlations of high dimensional variable spaces in new physics areas. This method is applied in the search for heavy neutrinos at LEP200. We show that the extracted knowledge improves the distinction between heavy neutrino candidates and background.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jochen Dahm, C. Voigt, K.-H. Becks, and J. Drees "Feature extraction using self-organizing networks", Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); https://doi.org/10.1117/12.205113
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