Neural networks have been applied in various fields from signal processing, pattern
recognition, associative memory to artificial intelligence. Recently, nanoscale memristor has …

In this paper, an online self-organizing fuzzy modified least-square (SOFMLS) network is
proposed. The algorithm has the ability to reorganize the model and adapt itself to a …

This paper proposes a self-evolving interval type-2 fuzzy neural network (SEIT2FNN) with
online structure and parameter learning. The antecedent parts in each fuzzy rule of the …

In this paper, a Takagi-Sugeno-Kang (TSK)-type-based self-evolving compensatory interval
type-2 fuzzy neural network (FNN)(TSCIT2FNN) is proposed for system modeling and noise …

In this paper, the synchronization control of a general class of memristor-based recurrent
neural networks with time delays is investigated. A delay-dependent feedback controller is …

This paper proposes a recurrent self-evolving fuzzy neural network with local feedbacks
(RSEFNN-LF) for dynamic system processing. A RSEFNN-LF is composed of zero-order or …

In recent years, multi-stable origami structures have garnered increasing attention for their
applications in dynamic scenarios such as robotic arm motions, impact energy absorption …

In this study, the trajectory tracking problem of robotic arms is considered. To solve this
problem, two novel modified optimal controllers based on neural networks are proposed …

Neural networks (NNs) have numerous applications to online processes, but the problem of
stability is rarely discussed. This is an extremely important issue because, if the stability of a …

In this paper, we propose a new passive weight learning law for switched Hopfield neural
networks with time-delay under parametric uncertainty. Based on the proposed passive …