New error bounds for linear complementarity problems of Nekrasov matrices and B-Nekrasov matrices
arXiv:1606.0683836 citationsh-index: 25
Originality Synthesis-oriented
AI Analysis
Provides tighter error bounds for a specific class of matrices, offering incremental improvement for researchers working on linear complementarity problems.
The paper derives new error bounds for linear complementarity problems involving Nekrasov and B-Nekrasov matrices, demonstrating through numerical examples that these bounds improve upon existing ones from Garcia-Esnaola and Pena in certain cases.
New error bounds for the linear complementarity problems are given respectively when the involved matrices are Nekrasov matrices and B-Nekrasov matrices. Numerical examples are given to show that new bounds are better respectively than those provided by Garcia-Esnaola and Pena in [15,16] in some cases.