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Generalizing Inverse Perspective
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05), 2005Inverse perspective mapping schemes have been presented in the past as frameworks in which autonomous navigation could be performed on flat surfaces, using optical flow as the main percept. We propose a generalization of these models for uneven terrains.
Mohamed Kotb, Steven S. Beauchemin
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On computing generalized inverses
Computing, 1969A method for computing the generalized inverse of a matrix is described, which makes use of elementary orthogonal matrices and theGaussian elimination. The method also yields orthonormal bases for the ranges and the null spaces of the matrix and the generalized inverse.
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Geometry, Integrability and Quantization, 2021
In this survey paper we present some aspects of generalized inverses, which are related to inner and outer invertibility, Moore-Penrose inverse, the appropriate reverse order law, and Drazin inverse.
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In this survey paper we present some aspects of generalized inverses, which are related to inner and outer invertibility, Moore-Penrose inverse, the appropriate reverse order law, and Drazin inverse.
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The generalized inverse and inverse structure
Acta Crystallographica Section A, 1977When a structure in one space is projected or mapped or otherwise described in another space or 'language', then the transformation is usually irreversible. In the case of linear transformations a generalized inverse matrix exists even if the transformation matrix is rectangular or singular.
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Generalized Inverse of a Finite Graph
Fundamenta Informaticae, 1981We define the optimal generalized inverse of the directed graph, give its construction and prove that the graph has an inverse graph iff its optimal generalized inverse is its inverse. The construction of the optimal generalized inverse may be used in the preparation of the PERT networks by the computer.
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1990
Abstract Consider again the set of linear equations in n unknowns. We saw in Chapter 4 that when A is n × n and has a non-zero determinant, then the unique solution of (10.1) is x = Aȃ1 b, where Aȃ1 is the inverse of A. However, in Chapter 5 we studied the important problem of solving (10.1) when A is singular or rectangular.
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Abstract Consider again the set of linear equations in n unknowns. We saw in Chapter 4 that when A is n × n and has a non-zero determinant, then the unique solution of (10.1) is x = Aȃ1 b, where Aȃ1 is the inverse of A. However, in Chapter 5 we studied the important problem of solving (10.1) when A is singular or rectangular.
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On a new generalized inverse of matrices
, 2018M. Mehdipour, A. Salemi
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An efficient computation of generalized inverse of a matrix
Applied Mathematics and Computation, 2018Victor Y. Pan, F. Soleymani, L. Zhao
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