While the handling for temporally-varying linear equation (TVLE) has received extensive
attention, most methods focused on trading off the conflict between computational precision …

Adaptive gradient neural networks (AGNN) have been extensively employed as effective
models for addressing time-varying problems. However, the existing AGNN are convergent …

As the zeroing neural network (ZNN) approach needs human intervention to handle
temporally variant quadratic program (TVQP) problem, which results in less flexibility and …

Harmonic noise frequently arouses by the disturbances in industrial applications, which
would be a great threat to the security, stability and service life of equipment in some large …

It is known that gradient information plays an essential role in GNS (gradient neurodynamic
system) for finding the solution to static problems, and derivative information plays an …

Discrete time-varying linear matrix problems (DTVLMP) play an important role in the field of
artificial intelligence and control engineering. This article presents a direct solution to the …

To enhance the safety of direct physical interaction between humans and lower-limb
exoskeletons, the actuator of the lower-limb exoskeleton should possess compliance, force …

High precision and low complexity control algorithm plays an important role in the
develo** of the end-effector instrumentation of different robot manipulators. In order to …

Temporal-variant linear equations (TVLEs) are widely acknowledged for their pivotal role in
various engineering fields, offering a potent means to model dynamic processes and …

To improve the acceleration performance, a hybrid state-triggered discretization (HSTD) is
proposed for the adaptive gradient neural network (AGNN) for solving time-dependent linear …