Zhang neural networks for a set of linear matrix inequalities with time-varying coefficient matrix

• A special neural network model is designed for time-varying linear matrix inequality.
• Time-varying linear matrix inequality is converted to time-varying matrix equation.
• The neural network model is efficient and accurate for online time-varying problems.

Zhang neural networks (ZNN) model is developed for solving a set of time-varying linear matrix inequalities, referred to as Stein matrix inequality, which exploits the time-derivative information of time-varying coefficients. Computer simulation results show that the proposed ZNN model is efficient and superior for such kind of linear matrix inequalities (LMIs).