Implementação de Redes Neurais em FPGA para Estimação de Energia no Calorímetro Hadrônico do Experimento ATLAS
Mariana Resende, Melissa Santos Aguiar, Dabson Ferreira, Lucca Viccini, Mateus Faria, Luciano Filho, José de Seixas

DOI: 10.14209/sbrt.2021.1570724027
Evento: XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2021)
Keywords: Calorimetry Neural Networks FPGA
In High Energy Physics experiments it is possible to measure the energy of the generated fundamental particles by estimating the amplitude of the signal coming from the reading electronics in calorimeters. Recently, it was proposed the implementation in FPGA of a Neural Network with activation function by lookup table seeking the estimation of the amplitude of the Hadronic Calorimeter of the ATLAS Experiment, using a large quantity of embedded memory. In this paper, it is proposed the development of a circuit to approximate the activation function through Taylor Series, drastically reducing the use of internal memories, allowing a greater number of channels per chip.