0000000000424677

AUTHOR

J.l. Ortiz Arciniega

showing 1 related works from this author

FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions

2019

The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions sinc…

Calibration and fitting methods010308 nuclear & particles physicsSignal reconstructionComputer scienceCluster findingDetectorTime signal01 natural sciencesSignal030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineSignal-to-noise ratioAnalog signalPattern recognitionData processing methods0103 physical sciencesSimulation methods and programsInstrumentationDigital filterAlgorithmMathematical PhysicsEnergy (signal processing)Journal of Instrumentation
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