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Application of Swingler's Method for Analysis of Multicomponent Exponentials with Special Attention to Non-equispaced Data
Application of Swingler's Method for Analysis of Multicomponent Exponentials with Special Attention to Non-equispaced Data
Abstract
Swingler enhanced the work of Gardner to provide an elegant deconvolution method by which multiple summed exponential components might be resolved within time-domain data. Nevertheless, the application of the method remains limited owing to subtle complications that discourage many users. We present a tutorial and extend the approach to handle nonequispaced data. Finally the method’s limits are identified in the case of closely-spaced exponential components with added input noise.
Type
Conference Contribution
Type of thesis
Series
Citation
Hasan, R., & Scott, J. B. (2016). Application of Swingler’s Method for Analysis of Multicomponent Exponentials with Special Attention to Non-equispaced Data. In 2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA), 4-6 March 2016, Melaysia (pp. 12–15). Washington, DC, USA: IEEE. https://doi.org/10.1109/CSPA.2016.7515794
Date
2016
Publisher
IEEE
Degree
Supervisors
Rights
This is an author’s accepted version of an article published in the Proceedings of 2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA). © 2016 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.