This article is concerned with the local stabilization of neural networks (NNs) under
intermittent sampled-data control (ISC) subject to actuator saturation. The issue is presented …

The important topic of multistability of continuous-and discrete-time neural network (NN)
models has been investigated rather extensively. Concerning the design of associative …

This article aims at analyzing and designing the multivalued high-capacity-associative
memories based on recurrent neural networks with both asynchronous and distributed …

A unified associative memory model with a novel method for designing associative
memories is presented in this paper. Based on continuous recurrent neural networks …

This paper discusses the second-order globally nonlinear consensus in general multi-agent
directed networks with both non-time-delay and time-delay couplings. Some easily …

This paper presents two new design procedures for synthesizing autoassociative memory
and heteroassociative memory based on recurrent neural networks with different external …

Recent years have seen increased attention being given to recurrent neural networks in
associative memory applications. The activation function is the core of the recurrent neural …

Traditional biological neural networks lack the capability of reflecting variable synaptic
weights when simulating associative memory of human brains. In this paper, we investigate …

A new fractional-order cellular neural network (CNN) system is solved using the Adomian
decomposition method (ADM) with the hyperbolic tangent activation function in this paper …

This paper presents a novel method for designing associative memories based on discrete
recurrent neural networks to accurately memorize the networks׳ external inputs. In the …