Computing Intelligent in Circuit Synthesis

Detalhes bibliográficos
Autor(a) principal: Reis, Cecília
Data de Publicação: 2007
Outros Autores: Tenreiro Machado, J. A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/13461
Resumo: 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.
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spelling Computing Intelligent in Circuit SynthesisComputational intelligenceEvolutionary algorithmsSwarm intelligenceLogic circuits designThis 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.Repositório Científico do Instituto Politécnico do PortoReis, CecíliaTenreiro Machado, J. A.2019-04-08T14:09:24Z20072007-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/13461enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:49:00Zoai:recipp.ipp.pt:10400.22/13461Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:28:43.827680Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Computing Intelligent in Circuit Synthesis
title Computing Intelligent in Circuit Synthesis
spellingShingle Computing Intelligent in Circuit Synthesis
Reis, Cecília
Computational intelligence
Evolutionary algorithms
Swarm intelligence
Logic circuits design
title_short Computing Intelligent in Circuit Synthesis
title_full Computing Intelligent in Circuit Synthesis
title_fullStr Computing Intelligent in Circuit Synthesis
title_full_unstemmed Computing Intelligent in Circuit Synthesis
title_sort Computing Intelligent in Circuit Synthesis
author Reis, Cecília
author_facet Reis, Cecília
Tenreiro Machado, J. A.
author_role author
author2 Tenreiro Machado, J. A.
author2_role author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Reis, Cecília
Tenreiro Machado, J. A.
dc.subject.por.fl_str_mv Computational intelligence
Evolutionary algorithms
Swarm intelligence
Logic circuits design
topic Computational intelligence
Evolutionary algorithms
Swarm intelligence
Logic circuits design
description 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.
publishDate 2007
dc.date.none.fl_str_mv 2007
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