Surrogate Assisted Optimization for Low-Voltage Low-Power Circuit Design
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TLDR
Kriging-based surrogate models of circuits' performances were constructed and then used within a metaheuristic-based optimization kernel in order to maximize the circuits’ sizing.Abstract:
Low-voltage low-power (LVLP) circuit design and optimization is a hard and time-consuming task. In this study, we are interested in the application of the newly proposed meta-modelling technique to alleviate such burdens. Kriging-based surrogate models of circuits’ performances were constructed and then used within a metaheuristic-based optimization kernel in order to maximize the circuits’ sizing. The JAYA algorithm was used for this purpose. Three topologies of CMOS current conveyors (CCII) were considered to showcase the proposed approach. The achieved performances were compared to those obtained using conventional LVLP circuit sizing techniques, and we show that our approach offers interesting results.read more
Citations
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Proceedings ArticleDOI
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References
More filters
Book ChapterDOI
On the Experimental Attainment of Optimum Conditions
George E. P. Box,K. B. Wilson +1 more
TL;DR: The work described in this article is the result of a study extending over the past few years by a chemist and a statistician, which has come about mainly in answer to problems of determining optimum conditions in chemical investigations, but they believe that the methods will be of value in other fields where experimentation is sequential and the error fairly small.
Journal ArticleDOI
Biomimicry of bacterial foraging for distributed optimization and control
TL;DR: A computer program that emulates the distributed optimization process represented by the activity of social bacterial foraging is presented and applied to a simple multiple-extremum function minimization problem and briefly discusses its relationship to some existing optimization algorithms.
Journal ArticleDOI
Multiquadric equations of topography and other irregular surfaces
TL;DR: In this paper, a method of representing irregular surfaces that involves the summation of equations of quadric surfaces having unknown coefficients is described, and procedures are given for solving multiquadric equations of topography that are based on coordinate data.
Journal Article
A statistical approach to some basic mine valuation problems on the Witwatersrand
TL;DR: In this paper, the application of the lognormal curve to the frequency distribution of gold values is discussed, and some fundamental concepts in application of statistics to mine valuation on the Witwatersrand are discussed.
Journal ArticleDOI
Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems
TL;DR: The proposed algorithm is found to secure first rank for the ‘best’ and ‘mean’ solutions in the Friedman’s rank test for all the 24 constrained benchmark problems.