Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an
experimentally proven new computing paradigm. Analogic cellular computers based on …

In this contribution, the main guidelines that, in the opinion of the authors, will address
bioinspired technologies in the next future are discussed. The topics are related to some …

This paper presents challenges and opportunities related to the problem of diffusion
boundary determination and zone control via mobile actuator-sensor networks (MAS-net) …

In this paper, dynamical systems made up of locally coupled nonlinear units are used to
control the locomotion of bio-inspired robots and, in particular, a simulation of an insect-like …

This article focuses on the design of an adaptive event-triggered sampled-data control
(ETSDC) mechanism for synchronization of reaction-diffusion neural networks (RDNNs) with …

This study develops the space-time sampled-data control problem for memristor-based
reaction-diffusion neural networks (MRDNNs) using a memory event-triggering scheme …

This study focuses on the quasisynchronization problem for reaction–diffusion neural
networks (RDNNs) in the presence of deception attacks. Under deception attacks, a time …

In this work, we explore pattern formation dynamics across a diffusively coupled Memristor
Cellular Nonlinear Network (MCNN), which is composed of identical cells with locally active …

This paper presents an innovative wormlike robot controlled by cellular neural networks
(CNNs) and made of an ionic polymer-metal composite (IPMC) self-actuated skeleton. The …

The asymptotical synchronization in mean square of reaction–diffusion neural networks
(RDNNs) with random delays is studied in this article. By sampling on both the time domain …