Abstract
The problem of the automatic selection from background events of electron pairs due to gamma-ray conversion in a multiplate spark chamber is dealt with by means of a direct non-parametric pattern recognition method. The method is applied to the data obtained in a gamma-ray astronomy experiment using a balloon-borne optical spark chamber. A filter operation is initially introduced to exclude clearly evident spurious events; the remaining spark chamber images are then reduced to their most significant zone in order to lower time and cost of subsequent analysis. The feature selection is performed by using a “training set” of labeled events and the classification made introducing a pre-established linear threshold decision function. Results are presented giving the percent of correct classification as a function of the threshold value chosen.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
