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

文献情報

出版日 2018-05-14

DOI 10.1039/C7AN01941F

インパクトファクター 4.616

著者

D. Wang

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要旨

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.

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Analyst

CiteScore: 7.8

自己引用率: 5.6%

年間論文数: 653

Analyst publishes analytical and bioanalytical research that reports premier fundamental discoveries and inventions, and the applications of those discoveries, unconfined by traditional discipline barriers.

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

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