Multiobjective analog/RF circuit sizing using an improved brain storm optimization algorithm

Multiobjective analog/RF circuit sizing using an improved brain storm optimization algorithm This paper presents a multiobjective analog/RF circuit sizing tool using an improved brain storm optimization (IMBSO) algorithm with the purpose of analyzing the tradeoffs between competing performance specifications of analog/RF circuit block. A number of improvements are incorporated into IMBSO algorithm at different steps. At first, the clustering step of IMBSO algorithm is augmented with k-means $$++$$ + + seeding technique to select the initial cluster centroids while clustering using k-means clustering technique. As a second improvement, the proposed IMBSO algorithm makes use of random probabilistic decision-making of river formation dynamics scheme to select optimal cluster centroids during population generation step. As a third improvement, an adaptive mutation operator is incorporated inside the IMBSO algorithm to generate new population. Finally, two separate constraint handling techniques are employed to handle both boundary and functional constraints during analog/RF circuit optimization. The performance of the proposed IMBSO algorithm is demonstrated in finding optimal Pareto fronts among different performance specifications of a two-stage operational amplifier circuit, a folded cascode amplifier circuit and a low noise amplifier circuit. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Memetic Computing Springer Journals

Multiobjective analog/RF circuit sizing using an improved brain storm optimization algorithm

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Engineering; Mathematical and Computational Engineering; Artificial Intelligence; Complex Systems; Control, Robotics, Mechatronics; Bioinformatics; Applications of Mathematics
ISSN
1865-9284
eISSN
1865-9292
D.O.I.
10.1007/s12293-018-0262-9
Publisher site
See Article on Publisher Site

Abstract

This paper presents a multiobjective analog/RF circuit sizing tool using an improved brain storm optimization (IMBSO) algorithm with the purpose of analyzing the tradeoffs between competing performance specifications of analog/RF circuit block. A number of improvements are incorporated into IMBSO algorithm at different steps. At first, the clustering step of IMBSO algorithm is augmented with k-means $$++$$ + + seeding technique to select the initial cluster centroids while clustering using k-means clustering technique. As a second improvement, the proposed IMBSO algorithm makes use of random probabilistic decision-making of river formation dynamics scheme to select optimal cluster centroids during population generation step. As a third improvement, an adaptive mutation operator is incorporated inside the IMBSO algorithm to generate new population. Finally, two separate constraint handling techniques are employed to handle both boundary and functional constraints during analog/RF circuit optimization. The performance of the proposed IMBSO algorithm is demonstrated in finding optimal Pareto fronts among different performance specifications of a two-stage operational amplifier circuit, a folded cascode amplifier circuit and a low noise amplifier circuit.

Journal

Memetic ComputingSpringer Journals

Published: May 31, 2018

References

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