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An interactive genetic algorithm approach to MMIC low noise amplifier design using a layered encoding structure
conference contribution
posted on 2008-01-01, 00:00 authored by S Neoh, A Marzuki, N Morad, Chee Peng LimChee Peng Lim, Z AzizIn this paper, an interactive genetic algorithm (IGA) approach is developed to optimize design variables for a monolithic microwave integrated circuit (MMIC) low noise amplifier. A layered encoding structure is employed to the problem representation in genetic algorithm to allow human intervention in the circuit design variable tuning process. The MMIC amplifier design is synthesized using the Agilent Advance Design System (ADS), and the IGA is proposed to tune the design variables in order to meet multiple constraints and objectives such as noise figure, current and simulated power gain. The developed IGA is compared with other optimization techniques from ADS. The results showed that the IGA performs better in achieving most of the involved objectives.
History
Event
Evolutionary Computation. Congress (2008 : Hong Kong, China)Pagination
1571 - 1575Publisher
IEEE Computer SocietyLocation
Hong Kong, ChinaPlace of publication
Los Alamitos, Calif.Publisher DOI
Start date
2008-06-01End date
2008-06-06ISBN-13
9781424418220ISBN-10
1424418224Language
engPublication classification
E1.1 Full written paper - refereedTitle of proceedings
CEC 2008 : Proceedings of the IEEE Congress on Evolutionary ComputationUsage metrics
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