Modern Spectrum Analysis in NMR

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Influence of sample distribution radial number of samples fixed exp. weighted random
• “Coherences” in the sampling scheme • Nyquist theorem does not apply: basis functions are non-orthogonal • Convolution of the sampling spectrum (PSF) with the true spectrum
Page 2 and 3: Only method capable of determining
Page 4 and 5: Fourier Transform NMR Impulse FT Er
Page 6 and 7: Jean Jeener, 1971 Parametric sampli
Page 8 and 9: Super-resolution Higher sensitivit
Page 10 and 11: LP extrapolation reduces truncation
Page 12 and 13: Classifying methods periodicity ran
Page 14 and 15: S i (f 1 ,f 2 ,f 3 ) = s i (f 1 )
Page 16 and 17: Back projection, by analogy to CT K
Page 18 and 19: Entropy functionals for NMR Shannon
Page 20 and 21: When N = M, Parseval’s Theorem Ma
Page 22 and 23: • DFT can be applied to NUS data
Page 24 and 25: Weighted DFT: General case Radial F
Page 26 and 27: Different methods frequently give c
Page 28 and 29: BPR and MaxEnt give similar results
Page 30 and 31: A B Barna, Laue, et al., 1987 C
Page 34 and 35: Problem is tatamount to deconvoluti
Page 36 and 37: Improving dynamic range via additio
Page 38 and 39: Coupled evolution periods: radial s
Page 40 and 41: NUS artifacts can be viewed as alia
Page 42 and 43: RMS blurring 0 0.625 1.25
Page 44: NUS on oversampled grid 15 N chemic
Page 47 and 48: Depends on the aim (metric) Depend
Page 49 and 50: Special Thanks David Donoho Berkele

Modern Spectrum Analysis in NMR

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