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Improved convergence criterion for the ACA algorithm

Heldring, A.; Ubeda, E.; Rius, J.
Type of activity
Presentation of work at congresses
Name of edition
XIII Iberian Meeting on Computational Electromagnetics
Date of publication
Presentation's date
Book of congress proceedings
XIII Encuentro ibérico de electromagnetismo computacional 2019 [Recurs electrònic]: 2019 EIEC
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Project funding
Advanced Digital Signal Processing Solutions for New Radios Power and Computational Efficient Devices and Systems
Gas-detection gravimetric sensors based on piezoelectric AlN thin film electroacoustic resonators for harsh temperature applications (TEC2017-84817-C2-2-R)
Grup de teledetecció, antenes, microones i superconductivitat
Microwave, Millimeter and Terahertz Reconfigurable Integrated Wireless Antenna Systems for Communications and Sensing (TEC2016-78028-C3-1-P)
Unitat d'Excel·lència/'María de Maeztu/': Grup de recerca en Teledetecció, Antenes, Microones i Superconductivitat
The Adaptive Cross Approximation (ACA) algorithm is a well-established tool in numerical modelling, used for fast and accurate compression of interaction matrices. The tradeoff between efficiency and memory requirements on the one hand, and accuracy on the other, is governed by a precision threshold and an accompanying approximate convergence criterion. It has long been known that this convergence criterion is sometimes very unreliable, yet despite the widespread success of the ACA, no viable al...
Group of research
ANTENNALAB - Antennas and Wireless Systems Laboratory
CommSensLab-UPC - Centre Específic de Recerca en Comunicació i Detecció UPC