EXACT CLASSIFICATION OF NMR SPECTRA FROM NMR SIGNALS

Lehmann P.I.; Xavier A.; Andiat, ME; Longt, CAS

Keywords: magnetic resonance spectroscopy, nuclear magnetic resonance spectroscopy, Sum of exponentials, harmonic signals, signal classification, end-to-end classification, harmonic retrieval

Abstract

Nuclear magnetic resonance (NMR) spectroscopy is routinely used to study the properties of matter. Therefore, different materials can be classified according to their NMR spectra. However, the NMR spectra cannot be observed directly, and only the NMR signal, which is a sum of complex exponentials, is directly observable in practice. A popular approach to recover the spectrum is to perform harmonic retrieval, i.e., to reconstruct exactly the spectrum from the NMR signal. However, even when this approach fails, the spectrum might still be classified accurately. In this work, we model the spectrum as an atomic measure to study the performance of classifying the spectrum from the NMR signal, and to determine how it degrades in the presence of additive noise and changes in field intensity. Although we focus on NMR signals, our results are broadly applicable to sum-of-exponential signals. We show numerical results illustrating our claims.

Más información

Título según WOS: EXACT CLASSIFICATION OF NMR SPECTRA FROM NMR SIGNALS
Título según SCOPUS: EXACT CLASSIFICATION OF NMR SPECTRA FROM NMR SIGNALS
Título de la Revista: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Editorial: Institute of Electrical and Electronics Engineers Inc.
Fecha de publicación: 2024
Página de inicio: 9771
Página final: 9775
Idioma: English
DOI:

10.1109/ICASSP48485.2024.10446412

Notas: ISI, SCOPUS