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DC Field | Value | Language |
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dc.contributor.author | Vladik Kreinovich | en_US |
dc.contributor.author | Olga Kosheleva | en_US |
dc.contributor.author | Hung T. Nguyen | en_US |
dc.contributor.author | Songsak Sriboonchitta | en_US |
dc.date.accessioned | 2018-09-05T02:58:22Z | - |
dc.date.available | 2018-09-05T02:58:22Z | - |
dc.date.issued | 2016-01-01 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-84952684545 | en_US |
dc.identifier.other | 10.1007/978-3-319-27284-9_7 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84952684545&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/55603 | - |
dc.description.abstract | © Springer International Publishing Switzerland 2016. In many situations, we have an (approximately) linear dependence between several quantities.(Formula presented.) The variance v=σ2of the corresponding approximation error (Formula presented.) often depends on the values of the quantities x1,…,xn: v= v(x1,…,xn); the function describing this dependence is known as the skedactic function. Empirically, two classes of skedactic functions are most successful: multiplicative functions (Formula presented.) and exponential functions (Formula presented.).In this paper, we use natural invariance ideas to provide a possible theoretical explanation for this empirical success; we explain why in some situations multiplicative skedactic functions work better and in some exponential ones. We also come up with a general class of invariant skedactic function that includes both multiplicative and exponential functions as particular cases. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Invariance explains multiplicative and exponential skedactic functions | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 622 | en_US |
article.stream.affiliations | University of Texas at El Paso | en_US |
article.stream.affiliations | New Mexico State University Las Cruces | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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