Detail publikace

Detector for Nuclear Quadrupole Resonance Spectroscopy

Originální název

Detector for Nuclear Quadrupole Resonance Spectroscopy

Anglický název

Detector for Nuclear Quadrupole Resonance Spectroscopy

Jazyk

en

Originální abstrakt

Nuclear quadrupole resonant spectroscopy is method similar to nuclear magnetic resonant spectroscopy also called zero field NMR [1, 2]. The response signal magnitude is very low and it is immersed in to the noise. There can be used some methods to harvest signal from noise it can be matched receiver [3] or averaging. This authors describe detector for Nuclear quadrupole resonant spectroscopy based on statistic methods and probability of distribution, that allow to measure repetitive signals below noise level. The paper presents the mathematical model and practical solution of the detector, and problems such as the dynamic range and signal distortion based on the signal-to-noise ratio are also analyzed in the given context. If the time of signal occurrence is known, the repetitive signal below the noise level can be harvested out of noise by averaging because of the wanted signal is correlated therefor highlighted by averaging contrast to the noise which is not correlated so it is supressed by averaging. The same principle we can use in domain of digital signal. So the input signal can be converted to the digital representation. There is an comparator with a triggering level immersed in the noise so the comparator is flipping continuously and the probability of output values is affected by input signal. The output digital signal can be processed by FPGA.

Anglický abstrakt

Nuclear quadrupole resonant spectroscopy is method similar to nuclear magnetic resonant spectroscopy also called zero field NMR [1, 2]. The response signal magnitude is very low and it is immersed in to the noise. There can be used some methods to harvest signal from noise it can be matched receiver [3] or averaging. This authors describe detector for Nuclear quadrupole resonant spectroscopy based on statistic methods and probability of distribution, that allow to measure repetitive signals below noise level. The paper presents the mathematical model and practical solution of the detector, and problems such as the dynamic range and signal distortion based on the signal-to-noise ratio are also analyzed in the given context. If the time of signal occurrence is known, the repetitive signal below the noise level can be harvested out of noise by averaging because of the wanted signal is correlated therefor highlighted by averaging contrast to the noise which is not correlated so it is supressed by averaging. The same principle we can use in domain of digital signal. So the input signal can be converted to the digital representation. There is an comparator with a triggering level immersed in the noise so the comparator is flipping continuously and the probability of output values is affected by input signal. The output digital signal can be processed by FPGA.

BibTex


@inproceedings{BUT109256,
  author="Jiří {Chytil} and Radek {Kubásek}",
  title="Detector for Nuclear Quadrupole Resonance Spectroscopy",
  annote="Nuclear quadrupole resonant spectroscopy is method similar to nuclear magnetic
resonant spectroscopy also called zero field NMR [1, 2]. The response signal magnitude is very low
and it is immersed in to the noise. There can be used some methods to harvest signal from noise it
can be matched receiver [3] or averaging. This authors describe detector for Nuclear quadrupole
resonant spectroscopy based on statistic methods and probability of distribution, that allow to
measure repetitive signals below noise level. The paper presents the mathematical model and
practical solution of the detector, and problems such as the dynamic range and signal distortion
based on the signal-to-noise ratio are also analyzed in the given context. If the time of signal
occurrence is known, the repetitive signal below the noise level can be harvested out of noise by
averaging because of the wanted signal is correlated therefor highlighted by averaging contrast to
the noise which is not correlated so it is supressed by averaging. The same principle we can use
in domain of digital signal. So the input signal can be converted to the digital representation.
There is an comparator with a triggering level immersed in the noise so the comparator is flipping
continuously and the probability of output values is affected by input signal. The output digital
signal can be processed by FPGA.",
  booktitle="PIERS 2014 Guangzhou",
  chapter="109256",
  howpublished="online",
  number="1",
  year="2014",
  month="september",
  pages="1907--1910",
  type="conference paper"
}