In recent years, neural networks have become a common practice in academia for handling
complex problems. Numerous studies have indicated that complex problems can generally …

Nonlinear activation functions play an important role in zeroing neural network (ZNN), and it
has be proved that ZNN can achieve finite-time convergence when the sign-bi-power (SBP) …

A generalized Sylvester equation is a special formulation containing the Sylvester equation,
the Lyapunov equation and the Stein equation, which is often encountered in various fields …

The Lyapunov equation is widely employed in the engineering field to analyze stability of
dynamic systems. In this paper, based on a new evolution formula, a novel finite-time …

Tracking control of robot manipulators is a fundamental and significant problem in robotic
industry. As a conventional solution, the Jacobian-matrix-pseudo-inverse (JMPI) method …

Matrix inversion often arises in the fields of science and engineering. Many models for matrix
inversion usually assume that the solving process is free of noises or that the denoising has …

Following the idea of using first-order time derivatives, this paper presents a general
recurrent neural network (RNN) model for online inversion of time-varying matrices. Different …

We are introducing a model-free control and a control with a restricted model for finite-
dimensional complex systems. This control design may be viewed as a contribution to …

In this paper, the noise-suppressing zeroing neural network models (NSZNNMs) for online
solving time-varying matrix square roots problems (TVMSRPs) are revisited and redesigned …

Using neural networks to handle intractability problems and solve complex computation
equations is becoming common practices in academia and industry. It has been shown that …