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To that end, the authors leverage the Functional Unit Row (FUR) architecture, a coarse-grained reconfigurable classifier, and apply it to two medical benchmarks, the Pima and Thyroid data sets from the UCI Machine Learning Repository. While quick recovery from architectural changes was already demonstrated for the FUR architecture, the authors also introduce two reconfiguration schemes helping to reduce the magnitude of degradation after architectural reconfiguration.<\/p>","DOI":"10.4018\/jaras.2012100102","type":"journal-article","created":{"date-parts":[[2013,1,14]],"date-time":"2013-01-14T12:16:00Z","timestamp":1358165760000},"page":"17-31","source":"Crossref","is-referenced-by-count":0,"title":["Compensating Resource Fluctuations by Means of Evolvable Hardware"],"prefix":"10.4018","volume":"3","author":[{"given":"Paul","family":"Kaufmann","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Paderborn, Paderborn, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyrre","family":"Glette","sequence":"additional","affiliation":[{"name":"University of Oslo, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Platzner","sequence":"additional","affiliation":[{"name":"University of Paderborn, Paderborn, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jim","family":"Torresen","sequence":"additional","affiliation":[{"name":"University of Oslo, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jaras.2012100102-0","author":"A.Asuncion","year":"2007","journal-title":"UCI machine learning repository. 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