Discrete-time Recurrent Neural Network Algorithm with Different Discretization Formulas for Finding Solution of Discrete-Time Complex Division

In this paper, in order to solve discrete-time complex division, we propose several discrete-time recurrent neural network (DT-RNN) algorithms. First of all, the continuous-time complex division is transformed into matrix equation equivalently, which can be solved by the continuous-time recurrent neural network (CT-RNN) algorithm. Secondly, several discretization formulas developed by Taylor formula are used to establish the corresponding DT-RNN algorithms. Finally, numerical experiments are carried out, which present the feasibility and effectiveness of these DT-RNN algorithms.