For the existing repetitive motion generation (RMG) schemes for kinematic control of
redundant manipulators, the position error always exists and fluctuates. This article gives an …

Various zeroing neural network (ZNN) models have been investigated to address the
tracking control of robot manipulators for the capacity of parallel processing and nonlinearity …

Water environment time series prediction is important to efficient water resource
management. Traditional water quality prediction is mainly based on linear models …

Inspired by the nature of actual dynamics systems with time-varying parameters, varying-
parameter convergence differential neural network (termed as VP-CDNN) has been put …

It has been reported that some specially designed recurrent neural networks and their
related neural dynamics are efficient for solving quadratic programming (QP) problems in …

The zeroing neural network (ZNN) model, a powerful approach for addressing time-varying
problems, has been extensively applied in the calculation and optimization fields. In this …

This article proposes an improved general zeroing neural network model to suppress noise
and to enhance the real-time performance of solving TVQP problems. The proposed model …

In order to find the theoretical solution of a dynamic Sylvester equation (DSE) in noisy
environment, a robust fast convergence zeroing neural network (RFCZNN) is proposed in …

Recurrent neural networks have been reported as an effective approach to solve dynamic
Lyapunov equations, which widely exist in various application fields. Considering that a …

For solving complex-valued linear matrix equations with time-varying coefficients (CV-LME-
TVC) in the complex field, this article proposes a parameter-changing and complex-valued …