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Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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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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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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Sampling and Analysis of Animal Scent Signals
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[Spectrum peak detection algorithm based on trend accumulation without base deduction].

Menghan Jia1, Zhaoyan Hui1, Hui Zhang1

  • 1School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.

Se Pu = Chinese Journal of Chromatography
|July 6, 2021
PubMed
Summary

This study introduces a novel spectral peak detection algorithm that bypasses traditional baseline correction and classification. The new method accurately identifies peaks directly from raw chromatographic data, proving robust against noise and versatile for complex peak shapes.

Keywords:
discrete differenceno base deductionpeak detection algorithmsearching for peaks by traversingtrend accumulation

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Area of Science:

  • Chromatography technology
  • Analytical chemistry
  • Signal processing

Context:

  • Spectral peak detection is crucial in chromatography but challenged by noise interference.
  • Traditional algorithms involve complex smoothing, baseline correction, and peak classification.
  • Existing methods suffer from high complexity, low automation, and susceptibility to distortion.

Purpose:

  • To develop a novel spectral peak detection algorithm for chromatography.
  • To overcome limitations of traditional methods by omitting baseline correction and classification.
  • To directly detect spectral peaks from raw data curves.

Summary:

  • A new algorithm uses discrete difference, trend accumulation, and three-point location for direct spectral peak detection.
  • It omits baseline subtraction and peak classification, directly analyzing source data curves.
  • The algorithm accurately identifies peaks, is robust to noise, and handles complex peak morphologies.

Impact:

  • The proposed algorithm offers accurate positioning, clear structure, and enhanced stability and reliability.
  • It effectively distinguishes peak and base components in chromatographic data, even with noise.
  • Demonstrated effectiveness in analyzing nitrogen adsorption and desorption chromatographic curves.