DocumentCode :
3213112
Title :
Non-sorting genetic algorithm in the optimization of unity-gain cells
Author :
Gómez, Guerra- ; Tlelo-Cuautle, E. ; Reyes-Garcìa, C.A. ; Reyes-Salgado, G. ; de la Fraga, Luis G.
Author_Institution :
INAOE, Tonantzintla, Mexico
fYear :
2009
fDate :
10-13 Jan. 2009
Firstpage :
1
Lastpage :
6
Abstract :
An optimization system based on the multi-objective evolutionary technique NSGA-II is presented to automatically size unity-gain cells, namely: voltage and current followers, and voltage and current mirrors. These unity-gain cells are optimized in three performance objectives: gain, bandwidth and offset. The proposed optimization system uses HSPICE as circuit evaluator by including input and output resistances as constraints, besides by guaranteeing that all transistors are in saturation operation.
Keywords :
SPICE; genetic algorithms; HSPICE evaluator; bandwidth performance; current follower; current mirror; gain performance; multi-objective evolutionary technique; nonsorting genetic algorithm; offset performance; unity-gain cells optimization; voltage follower; voltage mirror; Carbon capture and storage; Circuit simulation; Circuit synthesis; Cities and towns; Computer science; Genetic algorithms; Mirrors; Performance gain; User-generated content; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering, Computing Science and Automatic Control,CCE,2009 6th International Conference on
Conference_Location :
Toluca
Print_ISBN :
978-1-4244-4688-9
Electronic_ISBN :
978-1-4244-4689-6
Type :
conf
DOI :
10.1109/ICEEE.2009.5393478
Filename :
5393478
Link To Document :
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