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