NMR spectra can be reconstructed using entropy maximization algorithms
Multiple studies demonstrate that entropy maximization (MaxEnt) algorithms can successfully reconstruct high-resolution nuclear magnetic resonance (NMR) spectra, particularly from short or nonuniformly sampled data records.
The claim states that NMR spectra can be reconstructed using entropy maximization algorithms. Papers [1], [5], and [7] explicitly discuss and demonstrate the application of maximum entropy (MaxEnt) methods for reconstructing NMR spectra, particularly addressing limitations of standard Fourier transforms with short or nonuniformly sampled data. None of the papers refute the claim. Therefore, the balance verdict is SUPPORTED.
J. Hoch, M. Maciejewski, M. Mobli, A. Schuyler, A. S. Stern. Maximum Entropy Reconstruction and Nonuniform Sampling in Multidimensional NMR. 2014. https://doi.org/10.1021/ar400244v
This paper reviews maximum entropy (MaxEnt) reconstruction as a prominent non-Fourier method for obtaining high-resolution NMR spectra from short or nonuniformly sampled data records.
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Worley B. Convex accelerated maximum entropy reconstruction.. 2016. https://doi.org/10.1016/j.jmr.2016.02.003
This study presents an accelerated convex optimization algorithm (CAMERA) specifically designed to reliably reconstruct nonuniformly sampled NMR datasets using the principle of maximum entropy.
P J Hore. Maximum entropy and nuclear magnetic resonance. 1991. https://doi.org/10.1093/oso/9780198539414.003.0003
This historical work establishes the foundational use of the maximum entropy method as an alternative to Fourier transformation in NMR spectroscopy.
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