Automated abstraction of nonlinear analog circuits to reliable set-valued models with reduced overapproximation

Autor:	Markus Olbrich, Malgorzata Rechmal-Lesse, Gerald Alexander Koroa, Yeremia Gunawan Adhisantoso
Rok vydání:	2021
Předmět:	010302 applied physics Computer science 020208 electrical & electronic engineering Computer Science::Software Engineering 02 engineering and technology Condensed Matter Physics 01 natural sciences Atomic and Molecular Physics and Optics Surfaces Coatings and Films Electronic Optical and Magnetic Materials Set (abstract data type) Nonlinear system TheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Computer Science::Programming Languages Nonlinear analog circuits Electrical and Electronic Engineering Safety Risk Reliability and Quality Algorithm Affine arithmetic Abstraction (linguistics)
Zdroj:	Microelectronics Reliability. 121:114119
ISSN:	0026-2714
DOI:	10.1016/j.microrel.2021.114119
Popis:	This paper tackles the analog and mixed-signal modeling for verification challenges. It proposes an adjustable automated modeling approach, which provides set-valued models with reduced overapproximation. The models reliably enclose parameter variations and modeling errors. The reduced overapproximation is obtained by computing the intersecting set of models with intervals and affine forms. The nonlinear circuit examples show a reduced overapproximation up to 86%.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1bfd686d3170e4e128f4b641067d3fd8 https://doi.org/10.1016/j.microrel.2021.114119 Zobrazit plný text záznamu Full Text from ScienceDirect