Three novel high-resolution nonlinear methods for fast signal processing

Abstract

Three new operationally different but mathematically equivalent, stable user-friendly and robust signal processing methods named decimated signal diagonalization, decimated linear predictor, and decimated Pade approximant are introduced. They are implemented for performing the spectral analysis on experimental data for ion cyclotron resonance spectroscopy and nuclear magnetic resonance spectroscopy. These parameter estimators are shown to possess several important advantages over the fast Fourier transform, which is a spectral estimator.