Extended HTLS methods for parameter estimation of multiple data sets modeled as sums of exponentials

In subspace-based parameter estimation of a single signal modeled as a sum of exponentially damped sinusoids, a variant of Kung´s method, called HTLS in nuclear magnetic resonance spectroscopy, achieves best resolution and accuracy. When more than one signal is to be quantified, the HTLS method can be extended in several ways. This paper presents several extended HTLS methods quantifying multiple signals and compares these methods in different scenarios by means of a simulation study to find out which and when is best suited