Results 41 to 50 of about 11,144 (308)
The Ouroboros of Memristors: Neural Networks Facilitating Memristor Programming
arXiv (2024).
Yu, Zhenming +5 more
openaire +3 more sources
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Special Memristor and Memristor-Based Compact Neuron Circuit
Implementing neuron circuit using memristor can be more effective thanks to some properties of memristor such as nonlinearity. For this reason, many memristor-based neuron circuits have been found in the literature. This study presents a memristor-based floating neuron circuit that exhibits different types of spikes.
Altan, Muhammet Alper +4 more
openaire +2 more sources
Memristor-Based Edge Detection Dataset
This is the data produced for the paper titled: Memristor-Based Edge Detection. In this study, we investigate the use of silicon dioxde memristors in edge detection.
Wing Ng (6762572) +3 more
core +1 more source
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa +19 more
wiley +1 more source
Integration of Low‐Voltage Nanoscale MoS2 Memristors on CMOS Microchips
This article presents the first monolithic integration of nanoscale MoS2‐based memristors into the back‐end‐of‐line of foundry‐fabricated CMOS microchips in a one‐transistor‐one‐resistor (1T1R) architecture. The MoS2‐based 1T1R cells exhibit forming‐free, nonvolatile resistive switching with ultra‐low operating voltages, low cycle‐to‐cycle variability ...
Jimin Lee +16 more
wiley +1 more source
Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing
A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication.
Changju Yang, Hyongsuk Kim
doaj +1 more source
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner +14 more
wiley +1 more source
This study demonstrates that memristors can replace conventional 2T–1C driving circuits with simplified 1T–1 m architectures by exploiting resistance switching. With ultra‐low switching voltages (< ±0.2 V) and multi‐level resistance states, the memristors precisely control the current injected into organic light‐emitting diodes (OLEDs).
Dong Hyun Kim +6 more
wiley +1 more source
Neuromorphic Engineering: From Neural Systems to Brain-Like Engineered Systems
Morabito FC, Andreou AG, Chicca E. Neuromorphic Engineering: From Neural Systems to Brain-Like Engineered Systems. Neural Networks.
Andreou, Andreas G. +2 more
core +1 more source

