Improved neural dynamics for online Sylvester equations solving

• A novel implicit dynamics with its electronic implementation is proposed.
• Superior convergence performance compared to the existing dynamics can be achieved.
• Computer simulative results demonstrate theoretical analysis.

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.