JOURNAL ARTICLE

An Automated Passive Analog Circuit Synthesis Framework using Genetic Algorithms

Abstract

In this work, we present a genetic algorithm based automated circuit synthesis framework for passive analog circuits. A procedure is developed for the simultaneous generation of both the topology and the component values for analog circuits comprising of R, L and C elements, from a given set of specifications. The novelty of the work pertains to two distinct advantages when compared to previous evolutionary search techniques having similar objectives. First of all, the selection procedure chooses prospective parent circuits for mating on the basis of comparable fitness values. Secondly, the crossover process comprises of exchanging well-defined subcircuits, encompassing the whole design space, between the two chosen parent circuits. This minimizes the production of faulty offspring circuits. Experiments conducted on two filter specifications show that the techniques adopted bring about a reduction in the search space and help in faster attainment of the design goal.

Keywords:
Computer science Crossover Electronic circuit Analogue electronics Algorithm Set (abstract data type) Novelty Genetic algorithm Filter (signal processing) Selection (genetic algorithm) Artificial intelligence Machine learning Engineering

Metrics

44
Cited By
5.04
FWCI (Field Weighted Citation Impact)
11
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Evolutionary Algorithms and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
VLSI and FPGA Design Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
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