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dc.contributor.authorMalik, Rahila
dc.contributor.authorAlam, Mehboob
dc.contributor.authorMuhammad, Shah
dc.contributor.authorDuraihem, Faisal Zaid
dc.contributor.authorMassoud, Yehia Mahmoud
dc.date.accessioned2022-04-19T05:56:39Z
dc.date.available2022-04-19T05:56:39Z
dc.date.issued2022-04-18
dc.identifier.citationMalik, R., Alam, M., Muhammad, S., Duraihem, F. Z., & Massoud, Y. (2022). Second-Order Arnoldi Reduction using Weighted Gaussian Kernel. IEEE Access, 1–1. https://doi.org/10.1109/access.2022.3167732
dc.identifier.issn2169-3536
dc.identifier.doi10.1109/ACCESS.2022.3167732
dc.identifier.urihttp://hdl.handle.net/10754/676310
dc.description.abstractModeling and design of on-chip interconnect continue to be a fundamental roadblock for high-speed electronics. The continuous scaling of devices and on-chip interconnects generates self and mutual inductances, resulting in generating second-order dynamical systems. The model order reduction is an essential part of any modern computer-aided design tool for prefabrication verification in the design of on-chip components and interconnects. The existing second-order reduction methods use expensive matrix inversion to generate orthogonal projection matrices and often do not preserve the stability and passivity of the original system. In this work, a second-order Arnoldi reduction method is proposed, which selectively picks the interpolation points weighted with a Gaussian kernel in the given range of frequencies of interest to generate the projection matrix. The proposed method ensures stability and passivity of the reduced-order model over the desired frequency range. The simulation results show that the combination of multi-shift points weighted with Gaussian kernel and frequency selective projection dynamically generates optimal results with better accuracy and numerical stability compared to existing reduction techniques.
dc.description.sponsorshipSupported by Mirpur University of Science and Technology (MUST), Mirpur - 10250, AJK, Pakistan, University of Poonch Rawalakot, AJK, 12350, Pakistan, Deanship of Scientific Research at King Saud University for funding this work through research group no.RG-1441-351 and Innovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Saudi Arabia
dc.publisherIEEE
dc.relation.urlhttps://ieeexplore.ieee.org/document/9758797/
dc.relation.urlhttps://ieeexplore.ieee.org/document/9758797/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9758797
dc.rightsArchived with thanks to IEEE Access, This work is licensed under a Creative Commons Attribution 4.0 License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectInterpolation points
dc.subjectNumerical methods
dc.subjectOn-Chip Interconnects
dc.subjectSecond-order model order reduction
dc.subjectSecond-order Arnoldi
dc.titleSecond-Order Arnoldi Reduction using Weighted Gaussian Kernel
dc.typeArticle
dc.contributor.departmentInnovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Saudi Arabia
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
dc.identifier.journalIEEE Access
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Mathematics, Mirpur University of Science and Technology (MUST), Mirpur - 10250, AJK, Pakistan
dc.contributor.institutionDepartment of Electrical Engineering, University of Poonch Rawalakot, Rawalakot - 12350, AJK, Pakistan
dc.contributor.institutionDepartment of Mathematics, College of Science, King Saud University, Riyadh, Saudi Arabia
kaust.personMassoud, Yehia Mahmoud
refterms.dateFOA2022-04-19T05:58:05Z
kaust.acknowledged.supportUnitInnovative Technologies Laboratories (ITL)


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Archived with thanks to IEEE Access, This work is licensed under a Creative Commons Attribution 4.0 License
Except where otherwise noted, this item's license is described as Archived with thanks to IEEE Access, This work is licensed under a Creative Commons Attribution 4.0 License