Results 11 to 20 of about 274 (109)
IEEE Access, 2021 Power-efficient data processing subsystems performing millions of complex concurrent arithmetic operations per second form part of today’s essential solution required to meet the growing demand of edge computing applications, given the volume of ...
Nagaraj Lakshmana Prabhu +1 more
doaj +1 more source
Variability in Resistive Memories
Advanced Intelligent Systems, Volume 5, Issue 6, June 2023., 2023 A comprehensive review of variability in resistive memories is presented. Experimental evidence of variability for resistive memories is described. Later on, different approaches to model this variability from the physical, behavioral, and stochastic viewpoints are presented.
Juan B. Roldán +19 more
wiley +1 more source
Quantum Conductance in Memristive Devices: Fundamentals, Developments, and Applications
Advanced Materials, Volume 34, Issue 32, August 11, 2022., 2022 Quantum conductance effects in memristive devices are reviewed, from fundamentals of electrochemical phenomena underlying memristive functionalities to ballistic electronic conduction transport in atomic‐sized conductive filaments. Related challenges in nanoscale metrology for the characterization of memristive phenomena at the nanoscale are analyzed ...
Gianluca Milano +12 more
wiley +1 more source
Advanced Electronic Materials, Volume 8, Issue 7, July 2022., 2022 Recent advances for emulating biological neurons have been made of complementary‐metal‐oxide‐semiconductor field‐effect transistors (C‐MOSFETs) and capacitors. Capacitor‐less artificial neuron is necessary for high neuronal density. This study represents a novel conductive‐bridge‐neuron emulating an integrate‐and‐fire function as an alternative to ...
Dong‐Won Kim +8 more
wiley +1 more source
Ex Situ Transfer of Bayesian Neural Networks to Resistive Memory‐Based Inference Hardware
Advanced Intelligent Systems, Volume 3, Issue 8, August 2021., 2021 It is experimentally demonstrated how resistive memory‐based edge inference can be achieved using Bayesian neural networks. Since, like resistive memory devices, Bayesian network parameters are random variables, a more natural pairing of device and algorithm is proposed.
Thomas Dalgaty +4 more
wiley +1 more source
Low‐Power Computing with Neuromorphic Engineering
Advanced Intelligent Systems, Volume 3, Issue 2, February 2021., 2021 Neuromorphic computing is intensively investigated for decreasing power consumption and enriching computation functions. A brief introduction on the characteristics of neuromorphic computing and an overview on emerging devices for low‐power neuromorphic computing are provided, and a few computation models for artificial neural networks and a few ...
Dingbang Liu, Hao Yu, Yang Chai
wiley +1 more source
Pragmatic OxRAM compact model ready to use for design studies
, 2023 International audienceWe propose a pragmatic OxRAM device compact model describing SET, RESET, read operations and accounting for variability. The model is implemented in Verilog-A and usable with standard SPICE simulator. The objective is not to provide
Lacord, Joris +5 more
core +1 more source
An Energy-Efficient Current-Controlled Write and Read Scheme for Resistive RAMs (RRAMs)
IEEE Access, 2020 Energy efficiency remains one of the main factors for improving the key performance markers of RRAMs to support IoT edge devices. This paper proposes a simple and feasible low power design scheme which can be used as a powerful tool for energy reduction ...
H. Aziza +4 more
doaj +1 more source
Compact modeling solutions for OxRAM memories
, 2013 International audienceEmerging non-volatile memories based on resistive switching mechanisms pull intense R&D efforts from both academia and industry.
Deleruyelle, Damien +9 more
core +1 more source
, 2021 International audienceWe present for the first time Si-doped HfO 2 -based OxRAM 16kbit arrays integrated in the BEOL of 28nm FDSOI CMOS, targeting low cost and low power embedded applications.
Carabasse, C. +59 more
core +1 more source