MATLAB Simulink Modeling of Zhang Neural Network Solving for Time-Varying Pseudoinverse in Comparison with Gradient Neural Network

A special kind of recurrent neural networks (RNN), i.e., Zhang neural networks (ZNN), has recently been proposed for online time-varying problems solving. In this paper, we generalize and investigate the Matlab Simulink modeling and verification of a ZNN model for online time-varying matrix pseudoinverse solving. Based on click-and-drag mouse operations, Simulink could be easily and conveniently used to model and simulate complicated neural systems in comparison with Matlab coding. For comparative purposes, the conventional gradient-based neural network (or termed gradient neural network, GNN) is also developed for the time-varying pseudoinverse solving. Matlab Simulink modeling results substantiate the feasibility and efficacy of ZNN on time-varying pseudoinverse solving.