@article{Bai2022, 
author = {Shunjie Bai},
title = {A tighter M-eigenvalue localization set for partially symmetric tensors and its an application},
year = {2022},
journal = {AIMS Mathematics},
volume = {7},
number = {4},
pages = {6084-6098},
keywords = {partially symmetric tensors, M-eigenvalues, localization sets, M-spectral radius},
url = {https://www.sciopen.com/article/10.3934/math.2022339},
doi = {10.3934/math.2022339},
abstract = {In this paper, a new M-eigenvalue inclusion set for a partially symmetric tensor is provided. It is proved that the new set is tighter than some existing M-eigenvalue inclusion sets. Based on the obtained results, an upper bound of the largest M-eigenvalue is given and a modified WQZ-algorithm is established which guarantees the generated converges to the largest M-eigenvalue of the tensor faster.}
}