Results 11 to 20 of about 9,355 (180)

Implementation of binarized neural networks immune to device variation and voltage drop employing resistive random access memory bridges and capacitive neurons [PDF]

open access: yesCommunications Engineering
Resistive Random Access Memories (ReRAM) arrays provides a promising basement to deploy neural network accelerators based on near or in memory computing.
Mona Ezzadeen   +12 more
doaj   +2 more sources

Fabrication of a Hole‐Type Vertical Resistive‐Switching Random‐Access Array and Intercell Interference Induced by Lateral Charge Spreading

open access: yesAdvanced Electronic Materials, 2023
A hole‐type vertical structure is adopted to fabricate a vertically stacked resistive switching random access memory (ReRAM) array. The vertical configuration is more advantageous in lowering the process cost and increasing integration density than the ...
Seung Soo Kim   +7 more
doaj   +1 more source

Conductance-Aware Quantization Based on Minimum Error Substitution for Non-Linear-Conductance-State Tolerance in Neural Computing Systems

open access: yesMicromachines, 2022
Emerging resistive random-access memory (ReRAM) has demonstrated great potential in the achievement of the in-memory computing paradigm to overcome the well-known “memory wall” in current von Neumann architecture.
Chenglong Huang   +4 more
doaj   +1 more source

Intrinsically Secure Non-Volatile Memory Using ReRAM Devices

open access: yesIEEE Access, 2022
The paper describes a device-level encryption approach for implementing intrinsically secure non-volatile memory (NVM) using resistive RAM (ReRAM). Data are encoded in the ReRAM filament morphology, making it robust to both electrical and optical probing
Junjun Huan   +5 more
doaj   +1 more source

High-Performance InGaZnO-Based ReRAMs [PDF]

open access: yesIEEE Transactions on Electron Devices, 2019
Amorphous indium–gallium–zinc oxide (IGZO) is one of the most promising oxide semiconductors for thin–film transistors and it has started to replace amorphous silicon in display drivers. However, attempts to use IGZO in resistive random–access memories (ReRAMs) are still scarce.
Pengfei Ma   +6 more
openaire   +3 more sources

PEROVSKITES AND OTHER FRAMEWORK STRUCTURE CRYSTALLINE MATERIALS (BOOK' FIRST PAGES AND PREFACE)

open access: yesMaterials and Devices, 2021
Perovskites are among the most famous materials due to their exceptional properties: they present nearly all existing types of interesting properties, in particular as ferroics or multiferroics, they may be insulators, (super)conductors, or ...
Saint-Grégoire P., Smirnov M.
doaj   +1 more source

A nanoscale analysis method to reveal oxygen exchange between environment, oxide, and electrodes in ReRAM devices

open access: yesAPL Materials, 2021
The limited sensitivity of existing analysis techniques at the nanometer scale makes it challenging to systematically examine the complex interactions in redox-based resistive random access memory (ReRAM) devices.
Horatio R. J. Cox   +7 more
doaj   +1 more source

Nano-intrinsic security primitives with redox-based resistive memory

open access: yesFrontiers in Communications and Networks, 2022
Physical unclonable function (PUF) exploits advantages of otherwise undesirable non-idealities to create physical systems that are difficult to copy even with the same manufacturing process.
Jeeson Kim
doaj   +1 more source

XMA2: A crossbar-aware multi-task adaption framework via 2-tier masks

open access: yesFrontiers in Electronics, 2022
Recently, ReRAM crossbar-based deep neural network (DNN) accelerator has been widely investigated. However, most prior works focus on single-task inference due to the high energy consumption of weight reprogramming and ReRAM cells’ low endurance issue ...
Fan Zhang   +5 more
doaj   +1 more source

Exploiting device-level non-idealities for adversarial attacks on ReRAM-based neural networks

open access: yesMemories - Materials, Devices, Circuits and Systems, 2023
Resistive memory (ReRAM) or memristor devices offer the prospect of more efficient computing. While memristors have been used for a variety of computing systems, their usage has gained significant popularity in the domain of deep learning.
Tyler McLemore   +5 more
doaj   +1 more source

Home - About - Disclaimer - Privacy