Gast ::
| Hauptseite > Online First > FPGA-Based Real-Time Waveform Classification and Reduction in Particle Detectors |
| Hauptseite > Online First > FPGA-Based Real-Time Waveform Classification and Reduction in Particle Detectors |
| Conference Presentation (After Call) | FZJ-2025-04469 |
;
2025
Abstract: The SHiP SBT self-triggered readout will process SiPM sum signals sampled at 800 MSPS and 12 bit resolution to extract calorimetric particle hit information. A waveform classification is being deployed on the readout FPGA to reduce the volume of transmitted data.The classification divides events into expected signal, expected noise or containing unexpected features applying different degrees of compression.In this study, we consider LUT-based neural-networks and address challenges of NN layout, footprint and performance. Preliminary planning indicates significant data reduction, easing constraints on infrastructure.
|
The record appears in these collections: |
PDF
Volltext