Design and Validation of Discrete-Time Zeroing Neural Network for Time-Dependent Linear System of Equation and Inequality

In this paper, the discrete-time form of zeroing neural network (ZNN) is proposed and studied for the time-dependent linear system of equation and inequality (TDLS-EI). Specifically, the numerical difference formula based on Taylor series expansion is presented. Then, through utilizing the Talyor difference formula to discretize the existing ZNN model, a novel discrete-time ZNN (DTZNN) model is built to address the TDLSEI. Numerical simulation is implemented to verify the superior and effective performance of the proposed DTZNN model.