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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://repozitorij.uni-lj.si/IzpisGradiva.php?id=159756"><dc:title>Towards smaller single-point failure-resilient analog circuits by use of a genetic algorithm</dc:title><dc:creator>Rojec,	Žiga	(Avtor)
	</dc:creator><dc:subject>analog circuits</dc:subject><dc:subject>analog circuit synthesis</dc:subject><dc:subject>circuit optimization</dc:subject><dc:subject>failure-resilience</dc:subject><dc:subject>circuit robustness</dc:subject><dc:description>Failure-resilient analog circuits are difficult to design, but artificial intelligence can help crawl the topology solution space. Us-ing evolutionary computation-based topology synthesis we evolve analog arcus tangent computational circuits, resilient to any rectifying diode or resistor high-impedance single failure or removal. We encode analog circuit topologies as individuals with an upper-triangular incident matrix. Circuits are evolved using a combined technique utilizing parts of NSGA-II and PSADE, based on a special three-dimensional robustness function. We show that topology size for a failure-resilient circuit can be classes smaller than hand-made component-redundancy-based solutions. Our best failure-resilient topology comprises six diodes, three resistors, and a voltage offset source.</dc:description><dc:date>2023</dc:date><dc:date>2024-07-23 14:59:17</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>159756</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
