AbstractFor A : Vn → Vm with arbitrary inner products in Vn and Vm, updating formulas are given for the least squares solution of Ax = b and for the pseudo-inverse AI; an iterative scheme is given to calculate AI starting from an arbitrary initial guess B.When applied to matrices and ordinary inner products are assumed formulas of Greville and Fletcher are obtained. It is shown how Fletcher's formulas may be constructed from Greville's
This is the first paper of a two-long series in which we study linear generalized inverses that mini...
One of the possible approaches for the solution of underdetermined linear least-squares problems in ...
Inverse matrices applied to analysis and minimization of systems of linear equation
AbstractAn orthogonalization procedure is given for a sequence of vectors having the special feature...
It is known that the computed least squares solution x of Ax=b, in the presence of the round-off err...
Orthogonalization algorithm for producing pseudo inverse of matrix, and realization of algorithm wit...
A modified matrix product is explained, and it is shown that this product defiles a group whose inve...
AbstractA generalized inverse of a linear transformation A: → , where and are arbitrary finite di...
AbstractFirst we show that the Moore-Penrose solution of an arbitrary system of linear equations is ...
AbstractLet Ax = y be consistent; let x0 = Gy be any minimum-norm solution satisfying (AG)′ = AG; an...
AbstractLet V and W be two real or complex spaces which, by means of the choice of an inner product,...
AbstractWe derive an explicit determinantal formula for the least squares solution of an overdetermi...
Given a Krein space H and B, C in L(H), L(H), the bounded linear operators on H, the minimization/ma...
AbstractWe extend the concepts, introduced by C.R. Rao for Euclidean norms, of minimum g-inverses an...
Given two Krein spaces H and K, a (bounded) closed-range operator C:H→K and a vector y∈K, the indefi...
This is the first paper of a two-long series in which we study linear generalized inverses that mini...
One of the possible approaches for the solution of underdetermined linear least-squares problems in ...
Inverse matrices applied to analysis and minimization of systems of linear equation
AbstractAn orthogonalization procedure is given for a sequence of vectors having the special feature...
It is known that the computed least squares solution x of Ax=b, in the presence of the round-off err...
Orthogonalization algorithm for producing pseudo inverse of matrix, and realization of algorithm wit...
A modified matrix product is explained, and it is shown that this product defiles a group whose inve...
AbstractA generalized inverse of a linear transformation A: → , where and are arbitrary finite di...
AbstractFirst we show that the Moore-Penrose solution of an arbitrary system of linear equations is ...
AbstractLet Ax = y be consistent; let x0 = Gy be any minimum-norm solution satisfying (AG)′ = AG; an...
AbstractLet V and W be two real or complex spaces which, by means of the choice of an inner product,...
AbstractWe derive an explicit determinantal formula for the least squares solution of an overdetermi...
Given a Krein space H and B, C in L(H), L(H), the bounded linear operators on H, the minimization/ma...
AbstractWe extend the concepts, introduced by C.R. Rao for Euclidean norms, of minimum g-inverses an...
Given two Krein spaces H and K, a (bounded) closed-range operator C:H→K and a vector y∈K, the indefi...
This is the first paper of a two-long series in which we study linear generalized inverses that mini...
One of the possible approaches for the solution of underdetermined linear least-squares problems in ...
Inverse matrices applied to analysis and minimization of systems of linear equation