ROCEWEA. matrix power series

Title of paper: A filtering technique for the matrix power series being near-sparse

Authors: Feng Wu, Li Zhu, Yuelin Zhao and Kailing Zhang

This work presents a new algorithm for matrix power series which is near-sparse, that is, there are a large number of near-zero elements in it. The proposed algorithm uses a filtering technique to improve the sparsity of the matrices involved in the calculation process of the Paterson-Stockmeyer (PS) scheme. Based on the error analysis considering the truncation error and the error introduced by filtering, the proposed algorithm can obtain similar accuracy as the original PS scheme but is more efficient than it. For the near-sparse matrix power series, the proposed method is also more efficient than the MATLAB built-in codes.


Type: MATLAB code

The algorithm proposed in this article: mase_filt.m;
And 'filt_norm.mexw64' is the filtration algorithm proposed in ‘High-performance computation of large sparse matrix exponential’.
10 test matrices: A1.mat ~ A10.mat


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