A project neural network for solving degenerate quadratic minimax problem with linear constraints

In this paper, a quadratic minimax problem with linear constraints is studied. The mixed linear constraints and the degeneracy are the two significant characters of the problem considered in this paper. On the basis of the project properties and Lyapunov method, we get the complete convergence and the finite-time convergence of the proposed neural network in this paper. Moreover, we get that the nonsingular parts of the output trajectories respect to Q₁₁ and Q₂₂ are exponentially convergent. Particularly, we also give some analysis to the degenerate quadratic minimax problem without constraints. Furthermore, four illustrative examples are given to show the necessity of the matrix H in the network to solve this problem and the superiority of the network in this paper.