{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T15:26:01Z","timestamp":1740151561091,"version":"3.37.3"},"reference-count":10,"publisher":"Wiley","license":[{"start":{"date-parts":[[2012,6,4]],"date-time":"2012-06-04T00:00:00Z","timestamp":1338768000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"DOI":"10.13039\/100005156","name":"Alexander von Humboldt Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100005156","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advances in Artificial Neural Systems"],"published-print":{"date-parts":[[2012,6,4]]},"abstract":"<jats:p>Independent component analysis (ICA) is an essential building block for data analysis in many applications. Selecting the truly meaningful components from the result of an ICA algorithm, or comparing the results of different algorithms, however, is nontrivial problems. We introduce a very general technique for evaluating ICA results rooted in information-theoretic model selection. The basic idea is to exploit the natural link between non-Gaussianity and data compression: the better the data transformation represented by one or several ICs improves the effectiveness of data compression, the higher is the relevance of the ICs. We propose two different methods which allow an efficient data compression of non-Gaussian signals: Phi-transformed histograms and fuzzy histograms. In an extensive experimental evaluation, we demonstrate that our novel information-theoretic measures robustly select non-Gaussian components from data in a fully automatic way, that is, without requiring any restrictive assumptions or thresholds.<\/jats:p>","DOI":"10.1155\/2012\/962105","type":"journal-article","created":{"date-parts":[[2012,6,5]],"date-time":"2012-06-05T06:57:56Z","timestamp":1338879476000},"page":"1-13","source":"Crossref","is-referenced-by-count":0,"title":["Measuring Non-Gaussianity by Phi-Transformed and Fuzzy Histograms"],"prefix":"10.1155","volume":"2012","author":[{"given":"Claudia","family":"Plant","sequence":"first","affiliation":[{"name":"400 Dirac Science Library, Florida State University, Tallahassee, FL 32306-4120, USA"}]},{"given":"Son Mai","family":"Thai","sequence":"additional","affiliation":[{"name":"Department for Informatics, Research Unit for Database Systems, University of Munich, Oettingenstra\u00dfe 67, 80538 Munich, Germany"}]},{"given":"Junming","family":"Shao","sequence":"additional","affiliation":[{"name":"Klinikum rechts der Isar der TUM, Ismaninger Stra\u00dfe 22, 81675 Munich, Germany"}]},{"given":"Fabian J.","family":"Theis","sequence":"additional","affiliation":[{"name":"Helmholtz Zentrum M\u00fcnchen, Ingolst\u00e4dter Landstra\u00dfe 1, 85764 Neuherberg, Germany"}]},{"given":"Anke","family":"Meyer-Baese","sequence":"additional","affiliation":[{"name":"400 Dirac Science Library, Florida State University, Tallahassee, FL 32306-4120, USA"}]},{"given":"Christian","family":"B\u00f6hm","sequence":"additional","affiliation":[{"name":"Department for Informatics, Research Unit for Database Systems, University of Munich, Oettingenstra\u00dfe 67, 80538 Munich, Germany"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1749-6632.2010.05888.x"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/72.761722"},{"year":"2001","key":"3"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1088\/0967-3334\/26\/1\/R02"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(00)00026-5"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2002.805480"},{"issue":"6","key":"18","doi-asserted-by":"crossref","first-page":"2743","DOI":"10.1109\/18.720554","volume":"44","year":"1998","journal-title":"IEEE Transactions on Information Theory"},{"issue":"1","key":"19","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/S0167-7152(99)00191-1","volume":"48","year":"2000","journal-title":"Statistics and Probability Letters"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1109\/34.879789"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1023\/A:1013550313321"}],"container-title":["Advances in Artificial Neural Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/archive\/2012\/962105.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/archive\/2012\/962105.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/archive\/2012\/962105.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T05:30:36Z","timestamp":1607578236000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/aans\/2012\/962105\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,6,4]]},"references-count":10,"alternative-id":["962105","962105"],"URL":"https:\/\/doi.org\/10.1155\/2012\/962105","relation":{},"ISSN":["1687-7594","1687-7608"],"issn-type":[{"type":"print","value":"1687-7594"},{"type":"electronic","value":"1687-7608"}],"subject":[],"published":{"date-parts":[[2012,6,4]]}}}