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In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
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Updated: Jan 21, 2026

An All-in-one Sample Holder for Macromolecular X-ray Crystallography with Minimal Background Scattering
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GHz sampling hardware implementation with sub-Nyquist coprime sampling rates.

Weifeng Wen1, Haoyue Yan2, Yijiu Zhao2

  • 1Institute of Fluid Physics, China Academy of Engineering Physics, Mianyang 621999, China.

The Review of Scientific Instruments
|August 3, 2019
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Summary
This summary is machine-generated.

This study introduces a sub-Nyquist coprime sampling system for sparse signals, enabling high-rate signal reconstruction from undersampled data using novel hardware and algorithms.

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Area of Science:

  • Signal Processing
  • Electrical Engineering
  • Data Acquisition

Background:

  • Sparse analog signals require efficient sampling methods to avoid aliasing and reduce data volume.
  • Traditional uniform sampling can be insufficient for wideband signals, necessitating advanced techniques.
  • Accurate measurement of timing differences is crucial for coprime sampling systems.

Purpose of the Study:

  • To implement a sub-Nyquist coprime sampling system for sparse signals.
  • To develop a multicoset signal reconstruction algorithm for processing coprime samples.
  • To demonstrate high-rate signal reconstruction from undersampled data.

Main Methods:

  • Utilizing a pair of uniform samplers with different frequencies for coprime sampling.
  • Employing a field-programmable gate array (FPGA) based module for time difference acquisition.
  • Regrouping nonuniform coprime sample sets into multicoset sample sets for reconstruction.
  • Applying a multicoset signal reconstruction algorithm.

Main Results:

  • Successful implementation of coprime sampling hardware and a reconstruction algorithm.
  • Accurate measurement of start time differences between samplers.
  • Reconstruction of wideband sparse analog signals from sub-Nyquist samples.
  • Achieved equivalent reconstruction rates in the gigahertz range.

Conclusions:

  • The developed sub-Nyquist coprime sampling system effectively reconstructs sparse signals at high rates.
  • The combination of coprime sampling hardware and multicoset reconstruction offers a viable solution for undersampled wideband signals.
  • Experimental results validate the system's performance for gigahertz-equivalent signal reconstruction.