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Authors: Ramezani, Azin
Date: 2016
Language: eng
Resource Type: Thesis MRes
Identifier: http://hdl.handle.net/1959.14/1261763
Description: Theoretical thesis.
Full Text: Full Text
Date: 2016
Language: eng
Resource Type: Thesis PhD
Identifier: http://hdl.handle.net/1959.14/1163992
Description: Empirical thesis.
Full Text: Full Text
Date: 2012
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/350298
Description: In this paper Self-Advising SVM, a new proposed version of SVM, is investigated for sleep apnea classification. Self-Advising SVM tries to transfer more information from training phase to the test pha ... More
Reviewed: Reviewed
Date: 2012
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/350234
Description: This paper presents a method for signals and features selection when classifying sleep apnea. This study uses a novel hierarchical parallel particle swarm optimization structure as proposed by the aut ... More
Reviewed: Reviewed
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