Application of Pradovera’s Algorithm for Adaptive Frequency Sampling in Electromagnetic Simulation

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/4988

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DC Field	Value	Language
dc.contributor.author	Shilpa, T N	-
dc.contributor.author	Sinha, Rakesh	-
dc.date.accessioned	2025-01-17T15:55:29Z	-
dc.date.available	2025-01-17T15:55:29Z	-
dc.date.issued	2024-12	-
dc.identifier.citation	The IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), Bengaluru, India, 17-19 December 2024	en_US
dc.identifier.uri	http://hdl.handle.net/2080/4988	-
dc.description	Copyright belongs to the proceeding publisher.	en_US
dc.description.abstract	In this paper, we have implemented Davide Pradovera’s minimal sampling algorithm for adaptive frequency sampling in electromagnetic simulation. This algorithm is basically a modified AAA (Adaptive Antoulas– Anderson) version. Compared to the conventional AAA algorithm, this approach does not require a prior user-defined dataset to find out the next frequency sample point while meeting the specified error criteria. Pradrovera has introduced a pseudo error to find out the next frequency sample in an adaptive way incorporating the AAA algorithm. MATLAB R2023a was used to demonstrate two examples of electromagnetic simulation. This algorithm shows outstanding accuracy and speed performance.	en_US
dc.subject	AAA (Adaptive Antoulas– Anderson) algorithm	en_US
dc.subject	Adaptive frequency sampling (AFS)	en_US
dc.subject	Electromagnetic Simulation	en_US
dc.title	Application of Pradovera’s Algorithm for Adaptive Frequency Sampling in Electromagnetic Simulation	en_US
dc.type	Article	en_US
Appears in Collections:	Conference Papers

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