AUTHOR=Herzog Sebastian , Zimmermann Roland S. , Abele Johannes , Luther Stefan , Parlitz Ulrich 

TITLE=Reconstructing Complex Cardiac Excitation Waves From Incomplete Data Using Echo State Networks and Convolutional Autoencoders

JOURNAL=Frontiers in Applied Mathematics and Statistics

VOLUME=Volume 6 - 2020

YEAR=2021

URL=https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2020.616584

DOI=10.3389/fams.2020.616584

ISSN=2297-4687

ABSTRACT=Echo state networks (ESNs) and convolutional autoencoders (CAEs) are applied to solve two data modelling tasks in cardiac dynamics: Recovering excitation patterns from from noisy, blurred or undersampled observations and reconstructing complex electrical excitation waves  from mechanical deformation. Both approaches provide satisfying solutions, but CAEs turned out to be superior to ESNs in terms of reconstruction errors.