ABSTRACT
Sampling truncation, i. e. sampling ends before signal decays to zero, introduces wiggle-like artifacts that impair the quality of nuclear magnetic resonance ( NMR) spectra. In multidimensional ( mD) NMR experiments, the first few hundred or less data points are commonly sampled in the indirect dimension, and the truncation is unavoidable. Apodization can suppress truncation artifacts with cost of line-broadening. Linear prediction is also beneficial to the reduction of truncation artifacts. The worst situation is in the constant time ( CT) type experiments, where the signal doesn ' t decay at all in the CT evolution dimension. In this contribution we proposed that, although iterative soft thresholding ( IST) was rarely used due to the difficult parameter tuning, it was particularly suitable to suppress the truncation artifacts in the CT type NMR experiments. The simulation and experiments were performed to show the performance of this method. And the processing result was compared with a method proposed recently.