Analog computing for real-time solution of time-varying linear equations

An implicit recurrent neural network model (IRNN) is proposed in this paper for solving on-line time-varying linear equations. Such a neural network can be implemented as analog circuits or VLSI. Excellent convergent properties have been revealed by careful theoretical analysis. In the specific case where the linear equation is obtained from a time-varying Sylvester equation, the proposed IRNN model coincides with some existing recurrent neural networks reported in recent literature, where simulation examples have been reported to demonstrate the effectiveness and efficiency.