Robust Frequency-Selective Knowledge-Based Parameter Estimation for NMR Spectroscopy
In many magnetic resonance spectroscopy (MRS) applications, one strives to estimate the parameters describing the signal to allow for more precise knowledge of the analyte. Typically, MRS signals are well modelled as a sum of damped sinusoids that has properties that are partly known a priori. FREEK, a recently proposed subspace-based parameter estimation method allows for inclusion of such prior
