2019
DOI: 10.1016/j.jocs.2018.12.009
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A fast singular value decomposition algorithm of general k-tridiagonal matrices

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Cited by 15 publications
(16 citation statements)
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“…In this section, we make a modification to the SVD algorithm of [30] to obtain the sorted list of singular values.…”
Section: Parallel Singular Value Decomposition For K-tridiagonal Matricesmentioning
confidence: 99%
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“…In this section, we make a modification to the SVD algorithm of [30] to obtain the sorted list of singular values.…”
Section: Parallel Singular Value Decomposition For K-tridiagonal Matricesmentioning
confidence: 99%
“…A recent direction in numerical computation research pertains to k-tridiagonal matrices [21][22][23][24][25][26][27][28][29], for which, important algorithms, such as block-diagonalization [21], matrix inverse [22,23,26] and singular value decomposition [30], are improved by several orders of magnitude. A k-tridiagonal matrix [22] T ∈ R n×n is a matrix whose elements lay only on its main and kth upper and lower diagonals, i.e., there are some d ∈ R n and a, b ∈ R n−k , such that…”
Section: Introductionmentioning
confidence: 99%
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“…Lebih lanjut, Borowska dan Lacinska [4] juga telah melakukan kajian terkait hubungan nilai eigen matriks toeplitz 2-tridiagonal dengan matriks toeplitz tridiagonal. Penelitian-penelitian terbaru yang secara khusus membahas tentang matriks Toeplitz k-Tridiagonal dapat ditemukan pada [5]- [8]. Beberapa pembahasan ini secara spesifik belum ada yang membahas tentang determinan matriks ktridiagonal.…”
Section: Pendahuluanunclassified