The volume, veracity, variability, and velocity of data produced from the ever increasing
network of sensors connected to Internet pose challenges for power management …

The stability analysis of recurrent neural networks (RNNs) with multiple equilibria has
received extensive interest since it is a prerequisite for successful applications of RNNs …

Memristor is an ideal electronic device used as an artificial nerve synapse due to its unique
memory function. This article presents a design of a new Hopfield neural network (HNN) that …

In this article, sinusoidal functions are introduced to a discrete map for hyperchaos
generation and attractor self-reproduction. The constructed map shares a unique structure …

In this paper, from a new perspective of flux and charge, we present in-depth analyses of two
ideal memristor emulators and the fifth-order memristive Chua's circuit constructed based on …

This paper addresses the global stabilization of fractional-order memristor-based neural
networks (FMNNs) with time delay. The voltage threshold type memristor model is …

The paper presents memristor crossbar architectures for implementing layers in deep neural
networks, including the fully connected layer, the convolutional layer, and the pooling layer …

Conventional Von Neumann computing architectures based on CMOS technology are
currently facing challenges termed “the heat and memory wall” in addition to the advent of …

Artificial neural networks (ANNs), such as the convolutional neural network (CNN) and long
short-term memory (LSTM), have high complexity and contain large numbers of parameters …

In the article, the Mittag-Leffler stability and application of delayed fractional-order
competitive neural networks (FOCNNs) are developed. By virtue of the operator pair, the …