Analysis of de-noising methods to improve the precision of the ILSF BPM electronic readout system

Shafiee, Mehdi; Feghhi, S.A.H.; Rahighi, J.

doi:10.1088/1748-0221/11/12/p12020

Cited by 10 publications

(6 citation statements)

References 9 publications

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“…A regression analysis was applied to the retrieved data from satellite and ground- temperature. These results are in good agreement with the literature (Almazroui et al, 2012;Namdari et al, 2018;Shafiee et al, 2016aShafiee et al, , 2016bSingh and Oh, 2007). Previous studies indicated that any increase in ambient air temperature causes a reduction in relative humidity, leading to a decrease in threshold wind speed to initiate dust emissions.…”

Section: Sand and Dust Storm And Severe Sand And Dust Storm Occurrences In Shalamchehsupporting

confidence: 92%

Destinations frequently impacted by dust storms originating from southwest Iran

Broomandi

Karaca

Güney

et al. 2021

Atmospheric Research

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Section: Sand and Dust Storm And Severe Sand And Dust Storm Occurrences In Shalamchehsupporting

confidence: 92%

Destinations frequently impacted by dust storms originating from southwest Iran

Broomandi

Karaca

Güney

et al. 2021

Atmospheric Research

View full text Add to dashboard Cite

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“…6. To remove this noise, we implemented a Symlets 4 wavelet filter in Matlab (Chavan et al 2011;Shafiee et al 2016) as shown by the reddish line in Fig. 5.…”

Section: Sipm Signal Experimental Resultsmentioning

confidence: 99%

A SiPM photon-counting readout system for Ultra-Fast Astronomy

Lau¹,

Chan²,

Shafiee³

et al. 2022

TheOJA

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Very little work has been done searching for astrophysical transient optical emission in the millisecond to nanosecond regime with significant sensitivity. We call this regime "Ultra-Fast Astronomy", or UFA. To investigate transients on as short time scales as possible, we developed our own customized readout system for a silicon photomultiplier (SiPM)-based UFA camera, intended for use on conventional astronomical telescopes. SiPMs, available in array packages for imaging a field, are capable of time-tagged single-photon detection in the visible wavelength range. Our readout system consists of 16 channels of 14-bit data logging. Each channel includes a 50-dB gain pre-amplifier, signal shaping circuits, an analogue front end, an analogue to digital converter, and a Xilinx UltraScale+ Field Programable Gate Array Multipurpose System on Chip (FPGA-MPSoC) board for data-logging. We show that our system successfully read out the data from SiPM at 16 ns intervals with a maximum power consumption of 300 mW per channel and capability to perform concurrent 16 channels readout.

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“…The denoising process consists of applying the wavelet decomposition to the raw data, thresholding the wavelet coefficients based on a set of rules, and applying the inverse wavelet transformation. The optimization of wavelet-based denoising requires a choice of mother wavelet and its scale as well as the threshold for the wavelet coefficients [17]. Table 1 lists the set of mother wavelets (including their various order and coefficient numbers) that were explored in this work.…”

Section: Traditional Denoising Methodsmentioning

confidence: 99%

Performance of a convolutional autoencoder designed to remove electronic noise from p-type point contact germanium detector signals

Anderson¹,

Basu²,

Martin³

et al. 2022

Preprint

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We present a convolutional autoencoder to denoise pulses from a p-type point contact highpurity germanium detector similar to those used in several rare event searches. While we focus on training procedures that rely on detailed detector physics simulations, we also present implementations requiring only noisy detector pulses to train the model. We validate our autoencoder on both simulated data and calibration data from an 241 Am source, the latter of which is used to show that the denoised pulses are statistically compatible with data pulses. We also show that the shaping time used to calculate energy with a trapezoidal filter can be significantly reduced while maintaining a comparable energy resolution. Under certain circumstances, our denoising method can improve the overall energy resolution. The methods we developed to remove electronic noise are straightforward to extend to other detector technologies. Furthermore, the latent representation from the encoder is also of use in quantifying shape-based characteristics of the signals. Our work has great potential to be used in particle physics experiments and beyond.

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Analysis of de-noising methods to improve the precision of the ILSF BPM electronic readout system

Cited by 10 publications

References 9 publications

Destinations frequently impacted by dust storms originating from southwest Iran

Destinations frequently impacted by dust storms originating from southwest Iran

A SiPM photon-counting readout system for Ultra-Fast Astronomy

Performance of a convolutional autoencoder designed to remove electronic noise from p-type point contact germanium detector signals

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