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dc.contributor.authorHyun, Seung Gyu
dc.date.accessioned2021-08-17 15:31:22 (GMT)
dc.date.available2021-08-17 15:31:22 (GMT)
dc.date.issued2021-08-17
dc.date.submitted2021-08-10
dc.identifier.urihttp://hdl.handle.net/10012/17215
dc.description.abstractLinear recurrent sequences are those whose elements are defined as linear combinations of preceding elements, and finding recurrence relations is a fundamental problem in computer algebra. In this paper, we focus on sequences whose elements are vectors over the ring A = K[x]/<x^d> of truncated polynomials. Finding the ideal of their recurrence relations has applications such as the computation of minimal polynomials and determinants of sparse matrices over A. We present three methods for finding this ideal: a Berlekamp-Massey-like approach due to Kurakin, one which computes the kernel of some block-Hankel matrix over A via a minimal approximant basis, and one based on bivariate Pade approximation. We propose complexity improvements for the first two methods, respectively by avoiding the computation of redundant relations and by exploiting the Hankel structure to compress the approximation problem. Then we confirm these improvements empirically through a C++ implementation, and we discuss the above-mentioned applications.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectlinear sequenceen
dc.subjectBerlekamp-Masseyen
dc.subjectbivariate polynomialen
dc.subjectexact computationen
dc.titleAlgorithms for Linearly Recurrent Sequences of Truncated Polynomialsen
dc.typeMaster Thesisen
dc.pendingfalse
uws-etd.degree.departmentDavid R. Cheriton School of Computer Scienceen
uws-etd.degree.disciplineComputer Scienceen
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeMaster of Mathematicsen
uws-etd.embargo.terms0en
uws.contributor.advisorSchost, Eric
uws.contributor.affiliation1Faculty of Mathematicsen
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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