DocumentCode :
3209163
Title :
Optimizing Method for Analog Circuit Design Using Adaptive Immune Genetic Algorithm
Author :
Xu, Haiqin ; Ding, Yongsheng
Author_Institution :
Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
fYear :
2009
fDate :
17-19 Dec. 2009
Firstpage :
359
Lastpage :
363
Abstract :
The design of an analog circuit is so complex that much time is required. To improve the speed and efficiency of evolutionary hardware design, this paper presented an adaptive immune genetic algorithm (AIGA). The optimization of the analog circuit is the optimization of multi-dimensional parameters, and the trade-off of all parameters. The genetic algorithm is suitable for the optimization of the multi-dimensional parameters and the immune algorithm is suitable for the improvement of diversity. So AIGA can improve the searching ability, adaptability and the convergence speed. As an example, the optimization of parameters of a low-pass filter is presented. From simulation results, we confirm that the proposed method is suitable for the optimizing of the analog circuit.
Keywords :
analogue circuits; circuit optimisation; circuit simulation; genetic algorithms; network synthesis; adaptive immune genetic algorithm; analog circuit design optimization; low-pass filter; multi-dimensional parameter optimization; Algorithm design and analysis; Analog circuits; Circuit synthesis; Convergence; Design optimization; Educational technology; Genetic algorithms; Hardware; Immune system; Textile technology; Analog circuit; Evolutionary hardware design; Genetic algorithm; Immune algorithm; Immune genetic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontier of Computer Science and Technology, 2009. FCST '09. Fourth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3932-4
Electronic_ISBN :
978-1-4244-5467-9
Type :
conf
DOI :
10.1109/FCST.2009.79
Filename :
5392895
Link To Document :
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