ArticleThe journal of physical chemistry. A2021
Extraction of Weak Spectroscopic Signals with High Fidelity: Examples from ESR.
Article in The journal of physical chemistry. A, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Detection of Mutation-Induced Conformational Changes in an Intrinsically Disordered Protein by Double Quantum Coherence Electron Spin Resonance Methodology.Journal of the American Chemical Society · 2026Article
- Optimal Wavelet Selection for Signal Denoising.IEEE access : practical innovations, open solutions · 2024Article
- Time-Frequency Analysis of Two-Dimensional Electron Spin Resonance Signals.The journal of physical chemistry. A · 2023Article
- A Simulation Independent Analysis of Single- and Multi-Component cw ESR Spectra.Magnetochemistry (Basel, Switzerland) · 2023Article
- Analysis of Small-Molecule Mixtures by Super-ResolvedThe journal of physical chemistry. A · 2022Article
- Hyperfine Decoupling of ESR Spectra Using Wavelet Transform.Magnetochemistry (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Noise impedes experimental studies by reducing signal resolution and/or suppressing weak signals. Signal averaging and filtering are the primary methods used to reduce noise, but they have limited effectiveness and lack capabilities to recover signals at low signal-to-noise ratios (SNRs). We utilize a wavelet transform-based approach to effectively remove noise from spectroscopic data. The wavelet denoising method we use is a significant improvement on standard wavelet denoising approaches. We demonstrate its power in extracting signals from noisy spectra on a variety of signal types ranging from hyperfine lines to overlapped peaks to weak peaks overlaid on strong ones, drawn from electron-spin-resonance spectroscopy. The results show that one can accurately extract details of complex spectra, including retrieval of very weak ones. It accurately recovers signals at an SNR of ∼1 and improves the SNR by about 3 orders of magnitude with high fidelity. Our examples show that one is now able to address weaker SNR signals much better than by previous methods. This new wavelet approach can be successfully applied to other spectroscopic signals.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.