Optimizing semiconductor devices by self-organizing particle swarm

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dc.creatorXie, Xiao-Feng
dc.creatorZhang, Wen-Jun
dc.creatorBi, De-Chun
dc.date2005-05-25
dc.date.accessioned2026-07-07T03:23:02Z
dc.date.available2026-07-07T03:23:02Z
dc.descriptionA self-organizing particle swarm is presented. It works in dissipative state by employing the small inertia weight, according to experimental analysis on a simplified model, which with fast convergence. Then by recognizing and replacing inactive particles according to the process deviation information of device parameters, the fluctuation is introduced so as to driving the irreversible evolution process with better fitness. The testing on benchmark functions and an application example for device optimization with designed fitness function indicates it improves the performance effectively.
dc.descriptionCongress on Evolutionary Computation, 2004. CEC2004. Volume: 2, On page(s): 2017- 2022 Vol.2
dc.identifierhttps://arxiv.org/abs/cs/0505067
dc.identifierhttp://arxiv.org/abs/cs/0505067
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32787
dc.subjectNeural and Evolutionary Computing
dc.titleOptimizing semiconductor devices by self-organizing particle swarm
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