Recurrent neural networks for solving systems of complex-valued linear equations

Recurrent neutral networks are presented for solving systems of linear equations involving complex-valued coefficients. The recurrent neural networks are shown to be able to generate unknown solutions of complex-valued linear equations. The configurations of the recurrent neural networks are described. An example is also discussed.