A great deal of attention has been paid to solve the system of tensor equations in recent
years for its applications in various fields. In this paper, the Kaczmarz-like method, which is …

This work, with its three parts, reviews the state-of-the-art of studies for the tensor
complementarity problem and some related models. In the first part of this paper, we have …

In this paper, we propose continuous time neural network and modified continuous time
neural networks for solving a multi-linear system with M-tensors. Theoretically, we prove that …

The existing discrete-time neural dynamics methods for solving the multilinear tensor
equation (MTE) with-tensor are all derived from the continuous-time one and depend on the …

The main propose of this paper is to develop two neural network models for solving
nonsingular multi-linear tensor system. Theoretical analysis shows that each of the neural …

The main purpose of this paper is devoted to solving the multi-linear systems by the
preconditioned methods based on the tensor splittings. We consider a new preconditioner I+ …

Tensor equations is a kind of important tensor optimization problems with higher order
nonlinear equations, which are widely used in engineering and economics. This paper is …

In this paper, we propose a new preconditioned SOR method for solving the multi-linear
systems whose coefficient tensor is an M M-tensor. The corresponding comparison for …

Based on the weak regular splitting of tensors, preconditioned technology has shown great
advantages in solving tensor equations with nonsingular (strong) ℳ‐tensors. In this article …

The analysis of the existence of solutions for the systems of polynomial equations is much
more difficult to handle in general. Nonetheless, we can still confirm the existence of some …