Semi-classical Signal Analysis (SCSA) is a signal representation algorithm utilizing the Schrödinger eigenvalue problem. The algorithm has found many applications, from signal processing to machine learning and denoising due to its adaptive and localized nature. So far, the algorithm’s design parameter was tuned heuristically, without using the knowledge of the quantum mechanical principles residing in the SCSA formulation. In this work, we extend the SCSA framework by calculating the bounds of the reconstruction parameter. The derived bounds are effectively the sampling theorem for SCSA, which is of paramount importance for the application of the theory. Moreover, guidelines towards an optimal choice of the parameter are provided, eliminating the heuristic scanning step.
|Original language||English (US)|
|Title of host publication||2020 28th European Signal Processing Conference (EUSIPCO)|
|State||Published - Dec 18 2020|