The problem of solving algebraic Riccati equations (AREs) and certain linear matrix
equations which arise from the ARE frequently occur in applied and pure mathematics …

This paper analyzes the existing zeroing neural network (ZNN) models from the perspective
of control theory. It proposes an exclusive ZNN model for solving the dynamic complex …

Complex time-dependent Lyapunov equation (CTDLE), as an important means of stability
analysis of control systems, has been extensively employed in mathematics and …

The online solving of a dynamic linear complex matrix equation (DLCME) is commonly
encountered in many fields, and it exists for lots of engineering applications. For solving the …

Dynamic neural networks are efficient for solving algebraic equations. Among them, the
gradient neural network (GNN) has the lowest model complexity. The conventional GNN …

In this article, a novel approach of utilizing an integral dynamic learning network (IDLN) is
presented for addressing a general time-varying Lyapunov matrix equation (TVLME). First, a …

Zeroing neural network (ZNN), an effective method for tracking solutions of dynamic
equations, has been developed and improved by various strategies, typically the application …

A family of zeroing neural networks based on new nonlinear activation functions is proposed
for solving various time-varying linear matrix equations (TVLME). The proposed neural …

Solving dynamic Sylvester matrix equations is a prevalent research topic and many methods
have been arisen to solve the dynamic Sylvester equation, but few of them consider the …

In many fields, the issue of solving the time-varying Sylvester equation (TVSE) is commonly
encountered. Consequently, finding its exact solution has become a research hotspot. In …