Alternative Sampling Densities in Non-Uniform Sampling

Non-uniform sampling (NUS) is more widely practiced, but many implementations either do not weight the distribution of samples, or follow exponential sampling densities. Weighting the sampling density in proportion  to the signal envelope provides intrinsic sensitivity enhancements (MRC, V49, 483-491, 2011). However sinusoidal weighting is a compelling alternative to exponential weighting matched to the signal decay (JBNMR, V58: 303-314, 2014). We now describe families of alternative densities as candidates to replace common exponential NUS weightings. Yielding equal intrinsic sensitivity to their exponential counterparts, these alternatives possess improved constraints on line shapes by distributing more samples beyond 1xT2. An algorithm to generate properly gapped sampling densities (JBNMR, V58: 303-314, 2014) is extended, and is also contrasted with deterministic NUS schedules.