AbstractThis paper deals with block diagonalization of partitioned (not necessarily square) matrices. The process is shown to be analogous to calculating eigenvalues and eigenvectors. Computer techniques and examples are provided. Several various types of applications are discussed including application to liver disease
AbstractIn this paper we described block algorithms for the reduction of a real symmetric matrix to ...
AbstractGeneralizing the notion of an eigenvector, invariant subspaces are frequently used in the co...
Generalizing the notion of an eigenvector, invariant subspaces are frequently used in the context of...
AbstractThis paper deals with block diagonalization of partitioned (not necessarily square) matrices...
AbstractGiven operators E, F, G, and H, defined in an abstract linear space, B, we form the matrix o...
AbstractA method for computing a complete set of block eigenvalues for a block partitioned matrix us...
AbstractIf a partitioned matrix X is close enough to being block diagonal it is proved that X is sim...
summary:We study block diagonalization of matrices induced by resolutions of the unit matrix into th...
AbstractThroughout the last decades, several results have been published in the area of the so-calle...
summary:We study block diagonalization of matrices induced by resolutions of the unit matrix into th...
The interplay between spectrum and structure of graphs is the recurring theme of the three more or l...
The interplay between spectrum and structure of graphs is the recurring theme of the three more or l...
The interplay between spectrum and structure of graphs is the recurring theme of the three more or l...
AbstractThe choice of partitioning the system matrix for a system of N linear ordinary differential ...
The notion of invariant subspaces is useful in a number of theoretical and practical applications. ...
AbstractIn this paper we described block algorithms for the reduction of a real symmetric matrix to ...
AbstractGeneralizing the notion of an eigenvector, invariant subspaces are frequently used in the co...
Generalizing the notion of an eigenvector, invariant subspaces are frequently used in the context of...
AbstractThis paper deals with block diagonalization of partitioned (not necessarily square) matrices...
AbstractGiven operators E, F, G, and H, defined in an abstract linear space, B, we form the matrix o...
AbstractA method for computing a complete set of block eigenvalues for a block partitioned matrix us...
AbstractIf a partitioned matrix X is close enough to being block diagonal it is proved that X is sim...
summary:We study block diagonalization of matrices induced by resolutions of the unit matrix into th...
AbstractThroughout the last decades, several results have been published in the area of the so-calle...
summary:We study block diagonalization of matrices induced by resolutions of the unit matrix into th...
The interplay between spectrum and structure of graphs is the recurring theme of the three more or l...
The interplay between spectrum and structure of graphs is the recurring theme of the three more or l...
The interplay between spectrum and structure of graphs is the recurring theme of the three more or l...
AbstractThe choice of partitioning the system matrix for a system of N linear ordinary differential ...
The notion of invariant subspaces is useful in a number of theoretical and practical applications. ...
AbstractIn this paper we described block algorithms for the reduction of a real symmetric matrix to ...
AbstractGeneralizing the notion of an eigenvector, invariant subspaces are frequently used in the co...
Generalizing the notion of an eigenvector, invariant subspaces are frequently used in the context of...
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