文章基本信息

标题：Input selection in ARX model estimation using group lasso regularization
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作者：Måns Klingspor ; Anders Hansson ; Johan Löfberg 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：15
页码：897-902
DOI：10.1016/j.ifacol.2018.09.080
语种：English
出版社：Elsevier
摘要：AbstractIn system identification, input selection is a challenging problem. Since less complex models are desireable, non-relevant inputs should be methodically and correctly discarded before or under the estimation process. In this paper we investigate an input selection extension in least-squares ARX estimation and show that better model estimates are achieved compared to the least-square ssolution, in particular, for short batches of estimation data.
关键词：KeywordsInput selectionSystem identificationARX-modelsARMAX-modelsSignal-to-noise ratio