Sparse matrix: Numerical Analysis, Matrix, Network Theory, Partial Differential Equation, Data Structure, Diagonal Matrix, Tridiagonal Matrix, Band Matrix, Cuthill-McKee Algorithm - Tapa blanda

 
9786130347482: Sparse matrix: Numerical Analysis, Matrix, Network Theory, Partial Differential Equation, Data Structure, Diagonal Matrix, Tridiagonal Matrix, Band Matrix, Cuthill-McKee Algorithm

Sinopsis

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In the subfield of numerical analysis a sparse matrix is a matrix populated primarily with zeros (Stoer & Bulirsch 2002, p. 619). The term itself was coined by Harry M. Markowitz. Conceptually, sparsity corresponds to systems which are loosely coupled. Consider a line of balls connected by springs from one to the next; this is a sparse system. By contrast, if the same line of balls had springs connecting every ball to every other ball, the system would be represented by a dense matrix. The concept of sparsity is useful in combinatorics and application areas such as network theory, of a low density of significant data or connections.

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Reseña del editor

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In the subfield of numerical analysis a sparse matrix is a matrix populated primarily with zeros (Stoer & Bulirsch 2002, p. 619). The term itself was coined by Harry M. Markowitz. Conceptually, sparsity corresponds to systems which are loosely coupled. Consider a line of balls connected by springs from one to the next; this is a sparse system. By contrast, if the same line of balls had springs connecting every ball to every other ball, the system would be represented by a dense matrix. The concept of sparsity is useful in combinatorics and application areas such as network theory, of a low density of significant data or connections.

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