Computing Intelligent in Circuit Synthesis

This paper is devoted to the synthesis of combinational logic circuits through computacional intelligence or, more precisely, using evolutionary algorithms, the Genetic and the memetic ALgorithm (GAs, MAs) and one swarm intelligence algorithm, the Particle Swarm Optimization (PSO). GAs are optimizat...

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Bibliographic Details
Main Author: Reis, Cecília (author)
Other Authors: Tenreiro Machado, J. A. (author)
Format: article
Language:eng
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10400.22/13461
Country:Portugal
Oai:oai:recipp.ipp.pt:10400.22/13461
Description
Summary:This paper is devoted to the synthesis of combinational logic circuits through computacional intelligence or, more precisely, using evolutionary algorithms, the Genetic and the memetic ALgorithm (GAs, MAs) and one swarm intelligence algorithm, the Particle Swarm Optimization (PSO). GAs are optimization and search techniques based on the principles os genetics and natural selection. MAs are evolutionary algorithms that include a stage of individual optimization as part of its search algorithm that starts with a population-based search algorithm that starts with a population of random solutions called particles. This paper presents the results for digital circuits design using the three above algorithms. The results show the statistical characteristics of this algorithms with respect to the number of generatons required to archieve the solutions. The article analyzes also a new fitness, function that includes an error discontinuity measure, which demonstrated to improved significantly the performance of the algorithm.