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Conference Paper: An adaptive dynamical low-rank tensor approximation scheme for fast circuit simulation

TitleAn adaptive dynamical low-rank tensor approximation scheme for fast circuit simulation
Authors
Issue Date2015
PublisherIEEE.
Citation
The IEEE 11th International Conference on ASIC (ASICON 2015), Chengdu, China, 3-6 November 2015. How to Cite?
AbstractTensors, as higher order generalization of matrices, have received growing attention due to their readiness in representing multidimensional data intrinsic to numerous engineering problems. This paper develops an efficient and accurate dynamical update algorithm for the low-rank mode factors. By means of tangent space projection onto the low-rank tensor manifold, the repeated computation of a full tensor Tucker decomposition is replaced with a much simpler solution of nonlinear differential equations governing the tensor mode factors. A worked-out numerical example demonstrates the excellent efficiency and scalability of the proposed dynamical approximation scheme.
Persistent Identifierhttp://hdl.handle.net/10722/216392

 

DC FieldValueLanguage
dc.contributor.authorBatselier, K-
dc.contributor.authorChen, Q-
dc.contributor.authorWong, N-
dc.date.accessioned2015-09-18T05:26:12Z-
dc.date.available2015-09-18T05:26:12Z-
dc.date.issued2015-
dc.identifier.citationThe IEEE 11th International Conference on ASIC (ASICON 2015), Chengdu, China, 3-6 November 2015.-
dc.identifier.urihttp://hdl.handle.net/10722/216392-
dc.description.abstractTensors, as higher order generalization of matrices, have received growing attention due to their readiness in representing multidimensional data intrinsic to numerous engineering problems. This paper develops an efficient and accurate dynamical update algorithm for the low-rank mode factors. By means of tangent space projection onto the low-rank tensor manifold, the repeated computation of a full tensor Tucker decomposition is replaced with a much simpler solution of nonlinear differential equations governing the tensor mode factors. A worked-out numerical example demonstrates the excellent efficiency and scalability of the proposed dynamical approximation scheme.-
dc.languageeng-
dc.publisherIEEE.-
dc.relation.ispartofIEEE International Conference on ASIC (ASICON)-
dc.rightsIEEE International Conference on ASIC (ASICON). Copyright © IEEE.-
dc.rights©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleAn adaptive dynamical low-rank tensor approximation scheme for fast circuit simulation-
dc.typeConference_Paper-
dc.identifier.emailBatselier, K: kbatseli@hku.hk-
dc.identifier.emailChen, Q: q1chen@hku.hk-
dc.identifier.emailWong, N: nwong@eee.hku.hk-
dc.identifier.authorityChen, Q=rp01688-
dc.identifier.authorityWong, N=rp00190-
dc.description.naturepostprint-
dc.identifier.hkuros253243-
dc.customcontrol.immutablesml 151221-

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