Chaoqian Li

Hailang Wu, Yonghe Liu, Bingxuan Yu et al.

Non-negative reduced biquaternion matrix factorization (NRBMF) uses the product of reduced biquaternion (RB) matrices to incorporate the non-negativity constraints of color image pixels into the factorization process. However, NRBMF mainly focuses on reconstruction accuracy and does not exploit the local geometric structure of image data, which may limit the discriminative ability of the learned low-dimensional features. To address this issue, we propose a graph regularized non-negative reduced biquaternion matrix factorization (GNRBMF) model for color image recognition. The proposed model incorporates a graph Laplacian regularizer into the reduced biquaternion coefficient matrix, encouraging nearby samples in the original space to have similar representations in the learned feature space. Meanwhile, GNRBMF retains the non-negativity-preserving property of NRBMF in the reduced biquaternion domain. To solve the optimization problem, a component-wise alternating projected gradient algorithm is derived, and its convergence properties are analyzed. Experimental results demonstrate that the proposed GNRBMF model achieves competitive or superior recognition performance in some tested settings.

Chaoqian Li, Pingfan Dai, Yaotang Li

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.

Chaoqian Li, Yaotang Li

C-eigenvalues of piezoelectric-type tensors which are real and always exist, are introduced by Chen et al. [1]. And the largest C-eigenvalue for the piezoelectric tensor determines the highest piezoelectric coupling constant. In this paper, we give two intervals to locate all C-eigenvalues for a given Piezoelectric-type tensor. These intervals provide upper bounds for the largest C-eigenvalue. Numerical examples are also given to show the corresponding results.

Chaoqian Li, Hui Pei, Aning Gao et al.

We focus on the estimating problem of the infinity norm of the inverse of Nekrasov matrices, give new bounds which involve a parameter, and then determine the optimal value of the parameter such that the new bounds are better than those in L. Cvetkovic et al. (2013). Numerical examples are given to illustrate the corresponding results.

Chaoqian Li, Mengting Gan, Shaorong Yang

A new error bound for the linear complementarity problem is given when the involved matrix is a B-matrix. It is shown that this bound is sharper than some previous bounds [C.Q. Li, Y.T. Li. Note on error bounds for linear complementarity problems for B-matrices, Applied Mathematics Letters, 57:108-113,2016] and [C.Q. Li, Y.T. Li. Weakly chained diagonally dominant B-matrices and error bounds for linear complementarity problems, to appear in Numer.Algor.].

Lei Gao, Chaoqian Li

A new error bound for the linear complementarity problem when the matrix involved is a B-matrix is presented, which improves the corresponding result in [C.Q. Li et al., A new error bound for linear complementarity problems for B-matrices. Electron. J. Linear Al., 31:476-484, 2016]. In addition some sufficient conditions such that the new bound is sharper than that in [M. Garca-Esnaola and J.M. Pena. Error bounds for linear complementarity problems for B-matrices. Appl. Math. Lett., 22:1071-1075, 2009] are provided.

Chaoqian Li, Suhua Li, Qingbing Liu et al.

By excluding some sets, which don't include any eigenvalue of a tensor, from some existing eigenvalue inclusion sets, two new sets are given to locate all eigenvalues of a tensor. And it is shown that these two sets are contained in the Geršgorin eigenvalue inclusion set of tensors provide by Qi (Journal of Symbolic Computation 2005; 40:1302-1324) and the Brauer-type eigenvalue inclusion set provide by Li et al. (Numer. Linear Algebra Appl. 2014; 21:39-50) respectively. Two sufficient conditions such that the determinant of a tensor is not zero are also provided.

Chaoqian Li, Yaotang Li

For a complex tensor A, Minimal Gersgorin tensor eigenvalue inclusion set of A is presented, and its sufficient and necessary condition is given. Furthermore, we study its boundary by the spectrums of the equimodular set and the extended equimodular set for A. Lastly, for an irreducible tensor, a numerical approximation to Minimal Gersgorin tensor eigenvalue inclusion set is given.

Chaoqian Li, Yaotang Li

The class of MB(MB0)-tensors, which is a generation of B(B0)-tensors and quasi-double B(B0)-tensors, is proposed. And we prove that an even order symmetric MB(MB0)-tensor is positive (semi-)definite. This provides a positive answer for the conjecture in Li and Li's paper [15] that an even order symmetric quasi-double B0-tensor is positive semi-definite.