Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108759
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorLui, LKH-
dc.creatorLee, CKM-
dc.date.accessioned2024-08-27T04:40:27Z-
dc.date.available2024-08-27T04:40:27Z-
dc.identifier.urihttp://hdl.handle.net/10397/108759-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Lui LKH, Lee CKM. Modelling of Earphone Design Using Principal Component Analysis. Applied Sciences. 2023; 13(17):9912 is available at https://doi.org/10.3390/app13179912.en_US
dc.subjectComputer-aided designen_US
dc.subjectEarphone designen_US
dc.subjectPrincipal component analysisen_US
dc.subjectRegression modelen_US
dc.subjectSound qualityen_US
dc.titleModelling of earphone design using principal component analysisen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume13-
dc.identifier.issue17-
dc.identifier.doi10.3390/app13179912-
dcterms.abstractThis research investigated a mathematical model of earphone design with principal component analysis. Along with simplifying the design problem, a predictive model for the sound quality indicators, namely, total harmonic distortion, power of output, range of frequency response, signal-to-noise ratio, impedance of the speaker, and headroom, was formulated. (1) Background: Earphone design is a difficult problem requiring excessive experience and know-how in the process. Therefore, this research was developed to formulate a predictive model to facilitate the design process. (2) Methods: A simplified model for the design was developed in previous research, while the sound quality indicators were found to be connected to the eight material-specific parameters. Simultaneously, a principal component analysis (PCA) was utilized to decrease the number of input variables and create a more convenient and streamlined model. (3) Results: The principal component analysis-based approach obtained suboptimal predictive accuracy for the sound quality indicators, but a simplified formulation was obtained. (4) Conclusions: Based on the development and comparison of the modelling approach, it can be seen that principal component analysis can be utilized to simplify the mathematical model of the earphone design problem with a trade-off of accuracy.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationApplied sciences, Sept 2023, v. 13, no. 17, 9912-
dcterms.isPartOfApplied sciences-
dcterms.issued2023-09-
dc.identifier.scopus2-s2.0-85170363672-
dc.identifier.eissn2076-3417-
dc.identifier.artn9912-
dc.description.validate202408 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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