2006 IEEE International Conference on Cluster Computing 2006
DOI: 10.1109/clustr.2006.311908
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A Parallel Algorithm for the Solution of the Deconvolution Problem on Heterogeneous Networks

Abstract: In this work we present a parallel algorithm for the solution of a least squares problem with structured matrices.

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Cited by 2 publications
(2 citation statements)
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“…0 are the singular values of M. Partition P by P = [P (1) , P (2) ], where P (1) ∈ M m×n and P (2) ∈ M m×(m−n) . Let U ∈ O(m + n) be defined by…”
Section: A Regularized Directional Derivative-based Newton Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…0 are the singular values of M. Partition P by P = [P (1) , P (2) ], where P (1) ∈ M m×n and P (2) ∈ M m×(m−n) . Let U ∈ O(m + n) be defined by…”
Section: A Regularized Directional Derivative-based Newton Methodsmentioning
confidence: 99%
“…The inverse problem of reconstructing a matrix from the given singular values, i.e. the inverse singular value problem (ISVP), has growing importance in many applications such as the optimal sequence design for direct-spread code division multiple access [39], the passivity enforcement in nonlinear circuit simulation [33], the constructions of Toeplitz-related matrices from prescribed singular values [1,2,13], the inverse problem in some quadratic group [27], and the construction of nonnegative, positive and anti-bisymmetric matrices with prescribed singular values [23,24,42] and others [30].…”
Section: Introductionmentioning
confidence: 99%