Title :
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
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;
Conference_Titel :
Circuits and Systems, 2000. Proceedings of the 43rd IEEE Midwest Symposium on
Conference_Location :
Lansing, MI
Print_ISBN :
0-7803-6475-9
DOI :
10.1109/MWSCAS.2000.951605
