Quantum-based interval selection of the Semi-classical Signal Analysis method

Evangelos Piliouras, Taous-Meriem Laleg-Kirati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


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 languageEnglish (US)
Title of host publication2020 28th European Signal Processing Conference (EUSIPCO)
ISBN (Print)978-1-7281-5001-7
StatePublished - Dec 18 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-12-22


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