Improved neural dynamics for online Sylvester equations solving

Abstract

A novel implicit dynamic system together with its electronic implementation is firstly proposed and investigated for online solution of Sylvester equations. In view of the success of recently-proposed Zhang implicit dynamics, our proposed model is also designed in the implicit-dynamical fashion. Compared to the existing neural dynamics, i.e., conventional gradient explicit dynamics and Zhang implicit dynamics, our implicit dynamic system can achieve superior global exponential convergence performance. Computer simulation results demonstrate theoretical analysis of our proposed dynamic model for real-time solution of Sylvester equations.