PoS - Proceedings of Science
Volume 343 - Topical Workshop on Electronics for Particle Physics (TWEPP2018) - Posters
FPGA Implementation of an Artificial Neural Network for Subatomic Physics Experiment Particles Recognition
R. Zhao*, A. Besson, C. Hu-guo, L.A. Perez perez, K. Jaaskelainen, M. Goffe and Y. Hu
Full text: pdf
Pre-published on: May 20, 2019
Published on: July 25, 2019
CMOS Pixel Sensors have been used in subatomic physics experiments for charged particles detection. In the International Linear Collider (ILC) vertex detector, the occupancy will be mainly driven by impacts coming from the beam background. This will have a huge impact to the data flow of the system. We propose a design of CMOS pixel sensors with on-chip Artificial Neural Network (ANN) to tag and remove these hits. It is based on different features of hits clusters. In this paper, we will describe the structure of an ANN implemented in an FPGA device. We will show and analyze the distribution of incident angles reconstructed by the ANN.
DOI: https://doi.org/10.22323/1.343.0066
How to cite

Metadata are provided both in "article" format (very similar to INSPIRE) as this helps creating very compact bibliographies which can be beneficial to authors and readers, and in "proceeding" format which is more detailed and complete.

Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.