Euler-discretized GZ-type complex neuronet computing real-time varying complex matrix inverse

In this paper, a GZ-type complex neuronet (generated by combining gradient dynamic system and Zhang dynamic system) is illustrated and discretized into an Euler-discretized (i.e., discretized by Euler forward rule) GZ-type complex neuronet for computing real-time varying complex matrix inverse. Simulation results not only show the efficacy of the proposed Euler-discretized GZ-type neuronet but also verify that the error pattern is square.