The design of modern convolutional artificial neural networks (ANNs) composed of formal
neurons copies the architecture of the visual cortex. Signals proceed through a hierarchy …

The purpose of this study is to summarize the pattern recognition (PR) and deep learning
(DL) artificial intelligence methods developed for the management of data in the last six …

In this paper, two novel and general predefined-time stability lemmas are given and applied
to the predefined-time synchronization problem of memristive complex-valued bidirectional …

In the existing affective associative memory neural network circuits, the change of emotions
in the affective associative learning and forgetting processes is abrupt and the intensity of …

Nowadays, neuromorphic systems based on memristors are considered promising
approaches to the hardware realization of artificial intelligence systems with efficient …

Motivated by recent increased interest in optimization algorithms for non-convex
optimization in application to training deep neural networks and other optimization problems …

In this study, we fabricate and characterize a Ti/TiO2/Si device with different dopant
concentrations on a silicon surface for neuromorphic systems. We verify the device stack …

Resistive random-access memory (RRAM) is a promising technology to develop nonvolatile
memory and artificial synaptic devices for brain-inspired neuromorphic computing. Here, we …

Given the limitations of von Neumann computing systems, we propose a high-performance
reservoir computing system as an alternative. These systems operate as neural networks …

The future generation of digital technology will heavily rely on power efficient non-volatile
resistive memory systems as a potential alternative to flash memory due to its limitations in …