This paper presents an adaptive neural control approach for nonstrict-feedback nonlinear
systems in presence of unmodeled dynamics, unknown control directions and input dead …

This paper investigates exponential stabilization of continuous-time dynamic systems
(CDSs) via event-based impulsive control (EIC) approaches, where the impulsive instants …

The problem of exponential stabilization and synchronization for fuzzy model of memristive
neural networks (MNNs) is investigated by using periodically intermittent control in this …

As information technology is moving toward the era of big data, the traditional Von-Neumann
architecture shows limitations in performance. The field of computing has already struggled …

As the amount of data has grown exponentially with the advent of artificial intelligence and
the Internet of Things, computing systems with high energy efficiency, high scalability, and …

In this paper, we discuss synchronization of discrete-time recurrent neural networks
(DRNNs) with time-varying delays via quantized sliding mode control. A feedback controller …

In this paper, we obtain novel chaotic behaviors using differential and integral operators with
power-law, exponential-decay and Mittag-Leffler law for the Shinriki's oscillator model. We …

This paper is concerned with the problems of projective synchronization for fuzzy memristive
neural networks (FMNNs) with pinning impulsive control. At first, the mathematical model of …

This paper investigates the stability and lag synchronization for memristor-based fuzzy
Cohen–Grossberg bidirectional associative memory (BAM) neural networks with mixed …

Pulse coupled neural network (PCNN) is a kind of visual cortex-inspired biological neural
network, which has been proved a powerful candidate in the field of digital image …