A robust noise tolerant zeroing neural network for solving time-varying linear matrix equations

of proposed ZNN flows is studied both in the presence of noise and without noise. Simulation tests demonstrate the effectiveness and domination of the suggested activation over already existing activation functions. Further, the introduced noise-tolerant ZNN model is applied in solving the Wheatstone bridge and output tracking control problem.