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dc.contributor.authorWang, Yong
dc.contributor.authorTeng, Zhaosheng
dc.contributor.authorWen, He
dc.contributor.authorLi, Jianmin
dc.contributor.authorMartinek, Radek
dc.date.accessioned2018-09-04T07:39:22Z
dc.date.available2018-09-04T07:39:22Z
dc.date.issued2017
dc.identifier.citationAdvances in electrical and electronic engineering. 2017, vol. 15, no. 5, p. 770-779 : ill.cs
dc.identifier.issn1336-1376
dc.identifier.issn1804-3119
dc.identifier.urihttp://hdl.handle.net/10084/131480
dc.description.abstractDue to conventional differential evolution algorithm is often trapped in local optima and premature convergence in high dimensional optimization problems, a State Evaluation Adaptive Differential Evolution algorithm (SEADE) is proposed in this paper. By using independent scale factor on each dimension of optimization problem, and evaluating the distribution of population on each dimension, the SEADE correct the control parameters adaptively. External archive and a moving window evaluation mechanism on evolution state are introduced in SEADE to detect whether the evolution is stagnation or not, and with the help of opposition-based population, the algorithm can jump out of local optima basins. The results of experiments on several benchmarks show that the proposed algorithm is capable of improving the search performance of high dimensional optimization problems. And it is more efficient in design FIR digital filter using SEADE than conventionalcs
dc.format.extent607634 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoencs
dc.publisherVysoká škola báňská - Technická univerzita Ostravacs
dc.relation.ispartofseriesAdvances in electrical and electronic engineeringcs
dc.relation.urihttp://dx.doi.org/10.15598/aeee.v15i5.2496cs
dc.rights© Vysoká škola báňská - Technická univerzita Ostrava
dc.rightsAttribution-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/*
dc.subjectDifferential Evolution (DE)cs
dc.subjectexternal archivecs
dc.subjectFIR filtercs
dc.subjectopposition-based populationcs
dc.subjectstate evaluationcs
dc.titleA State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Designcs
dc.typearticlecs
dc.identifier.doi10.15598/aeee.v15i5.2496
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs


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