| Full text | |
| Author(s): |
de Lima Moreto, Rodrigo Alves
;
Thomaz, Carlos Eduardo
;
Gimenez, Salvador Pinillos
Total Authors: 3
|
| Document type: | Journal article |
| Source: | IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS; v. 36, n. 10, p. 1620-1632, OCT 2017. |
| Web of Science Citations: | 4 |
| Abstract | |
Analog CMOS integrated circuits (ICs) designs depend typically on designer knowledge and experience, as such problems are multivariate and multiobjective, presenting many combinations of input variables to be investigated in order to meet the required specifications. Nowadays, the a posteriori approach is widely used to perform the optimization processes of analog CMOS ICs using evolutionary algorithms. However, these techniques are not totally able to explore potential solutions in specific regions of the Pareto front. Designers then have difficulty in choosing the best solution capable of achieving all desired specifications simultaneously among all the ones found. In this context, the a priori approach using fitness functions has become an important alternative method to overcome these issues of the a posteriori methodology. This paper aims to compare different fitness function profiles used in the a priori optimization processes to boost the effectiveness of the search processes in relation to robustness, accuracy, and yield in analog CMOS ICs designs. We show that the Gaussian profile, proposed here, applied to the lower limit, center value, and upper limit fitness functions is able to improve all the a priori optimization evolutionary techniques investigated, including the genetic, imperialist competitive, and shuffled frog leaping algorithms. (AU) | |
| FAPESP's process: | 12/10394-3 - Design, manufacture and electrical characterization of CMOS transconductance operational amplifiers by using an evolutionary system integrated to the spice (AGSPICE) |
| Grantee: | Rodrigo Alves de Lima Moreto |
| Support Opportunities: | Scholarships in Brazil - Doctorate |