Abstract
A class of matrices (H-matrices) has recently been introduced by one of the authors. These matrices have the following properties: (i) They are sparse in the sense that only few data are needed for their representation, (ii) The matrix-vector multiplication is of almost linear complexity, (iii) In general, sums and products of these matrices are no longer in the same set, but their truncations to the H-matrix format are again of almost linear complexity, (iv) The same statement holds for the inverse of an H-matrix.
The term “almost linear complexity” used above means that estimates are given by O(nlogα n). The logarithmic factor can be avoided by a further improvement, which is described in the present paper. We prove that the storage requirements and the cost of the matrix-vector multiplication is strictly linear in the dimension n, while still (full) system matrices of the boundary element method can be approximated up to the discretization error.
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Dedicated to Professor Karl-Heinz Hoffmann on the ocasion of his 60th birthday
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Hackbusch, W., Khoromskij, B., Sauter, S.A. (2000). On H 2-Matrices. In: Bungartz, HJ., Hoppe, R.H.W., Zenger, C. (eds) Lectures on Applied Mathematics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59709-1_2
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DOI: https://doi.org/10.1007/978-3-642-59709-1_2
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