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Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
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AES is a powerful analytical technique, especially effective when used with plasma sources, producing abundant spectra in characteristic emission lines. The Inductively Coupled Plasma (ICP), in particular, yields superior quantitative analytical data due to its high stability, low noise, low background, and minimal interferences under optimal experimental conditions. However, newer air-operated microwave sources are emerging as promising alternatives that could be more cost-effective than...
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An Efficient CS-Based Spectral Peak Search Method.

Bingbing Chen1,2, Yufa Sun1

  • 1School of Electronic and Information Engineering, Anhui University, Hefei 230061, China.

Sensors (Basel, Switzerland)
|September 23, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a compressed sensing (CS) spectral peak search algorithm for faster frequency domain analysis. The method accurately identifies spectral peaks with reduced computational complexity, improving signal processing efficiency.

Keywords:
FFTcompressed sensingspectral peak searchunderdetermined equation

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Area of Science:

  • Signal Processing
  • Compressed Sensing
  • Frequency Domain Analysis

Background:

  • Spectral peak search is crucial for frequency domain parametric methods.
  • Conventional methods can be computationally intensive and require full spectrum acquisition.

Purpose of the Study:

  • To propose a novel spectral peak search algorithm using compressed sensing (CS).
  • To achieve rapid and accurate estimation of spectral peaks with reduced complexity.

Main Methods:

  • Utilizes Fast Fourier Transform (FFT) for initial coarse estimation.
  • Employs iterative small-scale inner products to refine peak positions.
  • Integrates with existing frequency domain interpolation methods.

Main Results:

  • Directly captures exact spectral peak locations without full spectrum acquisition.
  • Reduces inner product operations by up to 70% when integrated with interpolation methods.
  • Demonstrates accurate results with low complexity for 1D and 2D signals.

Conclusions:

  • The proposed CS-based spectral peak search algorithm offers significant speed and efficiency improvements.
  • The algorithm provides a computationally efficient and accurate solution for spectral analysis.
  • It is easily adaptable for various signal processing applications.