Digital Signal Processing with Field Programmable Gate Arrays

Meyer-Baese, Uwe

doi:10.1007/978-3-540-72613-5

Cited by 192 publications

(5 citation statements)

References 138 publications

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“…Neutron and gamma-ray lobes are well separated from energies above 200 keV. As described above, the developed neutron/gamma-ray discrimination method was implemented to the DNG@NCBJ hardware with use of FPGA for real-time signal processing [19,20].…”

Section: Results Of Signal Processing With Matched Filtering Methodsmentioning

confidence: 99%

Development of a digital method for neutron/gamma-ray discrimination based on matched filtering

et al. 2016

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A: Neutron/gamma-ray discrimination is crucial for measurements with detectors sensitive to both neutron and gamma-ray radiation. Different techniques to discriminate between neutrons and gamma-rays based on pulse shape analysis are widely used in many applications, e.g., homeland security, radiation dosimetry, environmental monitoring, fusion experiments, nuclear spectroscopy. A common requirement is to improve a radiation detection level with a high detection reliability. Modern electronic components, such as high speed analog to digital converters and powerful programmable digital circuits for signal processing, allow us to develop a fully digital measurement system. With this solution it is possible to optimize digital signal processing algorithms without changing any electronic components in an acquisition signal path. We report on results obtained with a digital acquisition system DNG@NCBJ designed at the National Centre for Nuclear Research. A 2 × 2 EJ309 liquid scintillator was used to register mixed neutron and gamma-ray radiation from PuBe sources. A dedicated algorithm for pulse shape discrimination, based on real-time filtering, was developed and implemented in hardware. K: Detector control systems (detector and experiment monitoring and slow-control systems, architecture, hardware, algorithms, databases); Digital signal processing (DSP); Gamma detectors (scintillators, CZT, HPG, HgI etc) 1Corresponding author.

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Section: Results Of Signal Processing With Matched Filtering Methodsmentioning

confidence: 99%

Development of a digital method for neutron/gamma-ray discrimination based on matched filtering

et al. 2016

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“…In order to complete the discussion, a possible implementation for one of the proposed SR methods (SSF) is outlined at the end of this paper. The circuitry was developed in Hardware Description Language (HDL) [40] envisaging a straightforward implementation in modern FPGAs.…”

Section: The Sr Algorithmsmentioning

confidence: 99%

“…The signal 𝑟 [𝑛] represents the measured information from a single calorimeter sensor front-end output, after applying the free-running (an uninterrupted) Analog-to-Digital Converter (ADC). A cascade of registers, synchronous with the ADC clock, implements a shift-register structure [40], which is responsible for storing the latest 𝑀 digitized samples. The filter order (𝑀 −1) depends on both the calorimeter reference pulse-shape width and the signal pile-up intensity.…”

Section: Fir Filter Based Energy Estimationmentioning

confidence: 99%

Sparse Deconvolution Methods for Online Energy Estimation in Calorimeters Operating in High Luminosity Conditions

Teixeira,

Andrade,

de Seixas

2021

Preprint

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A: Energy reconstruction in calorimeters operating in high luminosity particle colliders has become a remarkable challenge. In this scenario, pulses from a calorimeter front-end output overlap to each other (pile-up effect), compromising the energy estimation procedure when no preprocessing for signal disentanglement is accomplished. Recently, methods based on signal deconvolution have been proposed for both online and offline reconstructions. For online processing, constraints concerning fast processing, memory requirements, and cost implementation limit the overall performance. Offline reconstruction allows the use of Sparse Representation (SR) theory to implement sophisticated Iterative Deconvolution (ID) methods. This paper presents ID methods based on SR algorithms whose computational cost is effective for online implementation. Using simulation data, current techniques were compared to the proposed SR ones for performance validation in the online environments. Analysis has shown that, despite the higher computational cost, when compared to standard methods, the increase in performance may justify the use of the proposed techniques, in particular for the Separable Surrogate Functional (SSF). which is shown to be feasible for implementation in modern FPGAs.

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“…In order to complete the discussion, a possible implementation for one of the proposed Sparse Representation methods (in this case, the Separable Surrogate Functional) is outlined at the end of the paper. The circuitry was developed in Hardware Description Language (HDL) [29] envisaging a straightforward implementation in Field-Programmable Gate Array (FPGA) technology [30].…”

Section: The Pile-up Effectmentioning

confidence: 99%

“…The signal 𝑟 [𝑛] represents the measured information from a single front-end calorimeter sensor, after applying the free-running (an uninterrupted) Analog-to-Digital Converter (ADC). A cascade of registers, synchronous with the ADC clock, implements a shift-register structure [30], which is responsible for storing the latest 𝑀 digitized samples. The filter order (𝑀 − 1) depends on both the calorimeter reference pulse-shape width and the signal pile-up intensity.…”

Section: Fir Filter Based Energy Estimationmentioning

confidence: 99%

Sparse deconvolution methods for online energy estimation in calorimeters operating in high luminosity conditions

Teixeira

Andrade²,

Seixas³

2021

J. Inst.

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Digital Signal Processing with Field Programmable Gate Arrays

Cited by 192 publications

References 138 publications

Development of a digital method for neutron/gamma-ray discrimination based on matched filtering

Development of a digital method for neutron/gamma-ray discrimination based on matched filtering

Sparse Deconvolution Methods for Online Energy Estimation in Calorimeters Operating in High Luminosity Conditions

Sparse deconvolution methods for online energy estimation in calorimeters operating in high luminosity conditions

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