کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8166070 1526226 2018 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Pulse discrimination with a Gaussian mixture model on an FPGA
موضوعات مرتبط
مهندسی و علوم پایه فیزیک و نجوم ابزار دقیق
پیش نمایش صفحه اول مقاله
Pulse discrimination with a Gaussian mixture model on an FPGA
چکیده انگلیسی
A Gaussian Mixture Model (GMM) based machine learning algorithm has been applied to the problem of gamma/neutron pulse shape discrimination (PSD). The algorithm has been successfully implemented on a standard PC as well as a field programmable gate array (FPGA). Here we describe the GMM classifier and its implementation on these two different types of hardware. We compare the performance of the algorithm on these two platforms against each other, along with other standard techniques applied in PSD. Our results show that the FPGA-based GMM classifier outperforms the standard PSD techniques in terms of classification accuracy at low particle energy and executes more quickly than its CPU-based counterpart.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 900, 21 August 2018, Pages 1-7
نویسندگان
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