Issue 11, 2018

Salient space detection algorithm for signal extraction from contaminated and distorted spectrum

Abstract

An algorithm for signal extraction from a contaminated and distorted spectrum is proposed. First, this algorithm combines the salient space of the spectrum and the statistical characteristics of the noise to detect signal regions at different scales. Second, it extracts signals by subtracting the baseline from the spectrum in the signal regions. The baseline is fitted by segmented polynomial functions. This algorithm has been applied to simulated and experimental data, and the results show that this algorithm can accurately and automatically extract signals with varying widths from a contaminated spectrum. This method minimizes the influence of baseline distortion and exhibits good anti-noise capability and high real-time performance.

Graphical abstract: Salient space detection algorithm for signal extraction from contaminated and distorted spectrum

Article information

Article type
Paper
Submitted
01 dec 2017
Accepted
22 apr 2018
First published
14 mei 2018
This article is Open Access
Creative Commons BY license

Analyst, 2018,143, 2656-2664

Salient space detection algorithm for signal extraction from contaminated and distorted spectrum

Y. W. Jia, S. Y. Sun, L. Yang and D. Wang, Analyst, 2018, 143, 2656 DOI: 10.1039/C7AN01941F

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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