An interactive genetic algorithm approach to MMIC low noise amplifier design using a layered encoding structure

Neoh, Siew Chin, Marzuki, Arjuna, Morad, Norhashimah, Lim, Chee Peng and Aziz, Zalina Abdul 2008, An interactive genetic algorithm approach to MMIC low noise amplifier design using a layered encoding structure, in CEC 2008 : Proceedings of the IEEE Congress on Evolutionary Computation, IEEE Computer Society, Los Alamitos, Calif., pp. 1571-1575.

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Title An interactive genetic algorithm approach to MMIC low noise amplifier design using a layered encoding structure
Author(s) Neoh, Siew Chin
Marzuki, Arjuna
Morad, Norhashimah
Lim, Chee Peng
Aziz, Zalina Abdul
Conference name Evolutionary Computation. Congress (2008 : Hong Kong, China)
Conference location Hong Kong, China
Conference dates 1-6 Jun. 2008
Title of proceedings CEC 2008 : Proceedings of the IEEE Congress on Evolutionary Computation
Editor(s) [Unknown]
Publication date 2008
Conference series Evolutionary Computation. Congress
Start page 1571
End page 1575
Total pages 5
Publisher IEEE Computer Society
Place of publication Los Alamitos, Calif.
Keyword(s) algorithm design and analysis
design optimization
encoding
genetic algorithms
integrated circuit noise
Summary In 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.
ISBN 1424418224
9781424418220
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30049263

Document type: Conference Paper
Collection: Institute for Frontier Materials
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