“…By the same reasoning as in the previous section, we obtain Equation (8). Thus, if for every (α, β) in S m,n,k, , we multiply both sides of Equation (8) by µ α,β t |α|−|β| and add up all these equalities, we obtain the following expression:…”
Section: Lemma 211mentioning
confidence: 89%
“…Solving parametric linear systems of equations is an interesting computational issue encountered, for example, when computing the characteristic solutions for differential equations (see [5]), when dealing with coloured Petri nets (see [13]) or in linear prediction problems and in different applications of operation research and engineering (see, for example, [6], [8], [12], [15] or [19] where the elements of the matrix have a linear affine dependence on a set of parameters). More general situations where the elements are polynomials in a given set of parameters are encountered in computer algebra problems (see [1] and [18]).…”
Section: Introductionmentioning
confidence: 99%
“…such that (1, 1, 0) is a concrete zero of our system and 1 t+3 (0, 8,6) is solution of the homogenous linear system defined by A.…”
Following Mulmuley's Lemma, this paper presents a generalization of the Moore-Penrose Inverse for a matrix over an arbitrary field. This generalization yields a way to uniformly solve linear systems of equations which depend on some parameters.
“…By the same reasoning as in the previous section, we obtain Equation (8). Thus, if for every (α, β) in S m,n,k, , we multiply both sides of Equation (8) by µ α,β t |α|−|β| and add up all these equalities, we obtain the following expression:…”
Section: Lemma 211mentioning
confidence: 89%
“…Solving parametric linear systems of equations is an interesting computational issue encountered, for example, when computing the characteristic solutions for differential equations (see [5]), when dealing with coloured Petri nets (see [13]) or in linear prediction problems and in different applications of operation research and engineering (see, for example, [6], [8], [12], [15] or [19] where the elements of the matrix have a linear affine dependence on a set of parameters). More general situations where the elements are polynomials in a given set of parameters are encountered in computer algebra problems (see [1] and [18]).…”
Section: Introductionmentioning
confidence: 99%
“…such that (1, 1, 0) is a concrete zero of our system and 1 t+3 (0, 8,6) is solution of the homogenous linear system defined by A.…”
Following Mulmuley's Lemma, this paper presents a generalization of the Moore-Penrose Inverse for a matrix over an arbitrary field. This generalization yields a way to uniformly solve linear systems of equations which depend on some parameters.
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