A hybrid genetic algorithm method for optimizing analog circuits

Author

Papadopoulos, S. ; Mack, R.J. ; Massara, R.E.

Author_Institution

Dept. of Electron. Syst. Eng., Essex Univ., Colchester, UK

Volume

1

fYear

2000

fDate

2000

Firstpage

140

Abstract

An approach is presented for the automated sizing of analog circuits based upon a combination of a genetic algorithm (GA) with a least squares (Gauss-Newton) gradient search. The method combines the global-search properties of the GA with the fast local convergence properties of the least squares method to produce a circuit design from random initial component values in a reduced time compared to the application of a direct GA method, or a restart least squares algorithm. Results are presented to demonstrate the application of the method in the design of both passive and active circuits

Keywords

Newton method; active networks; analogue integrated circuits; circuit optimisation; genetic algorithms; least squares approximations; passive networks; Gauss-Newton search; active circuits; analog circuits; automated sizing; circuit optimization; global-search properties; hybrid genetic algorithm method; least squares gradient search; local convergence properties; passive circuits; random initial component values; Active circuits; Analog circuits; Circuit synthesis; Convergence; Design methodology; Genetic algorithms; Least squares methods; Newton method; Optimization methods; Recursive estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2000. Proceedings of the 43rd IEEE Midwest Symposium on

Conference_Location

Lansing, MI

Print_ISBN

0-7803-6475-9

Type

conf

DOI

10.1109/MWSCAS.2000.951605

Filename

951605