HfO2-Based OxRAM Devices as Synapses for Convolutional Neural Networks
In this paper, the use of HfO 2-based oxide-based resistive memory (OxRAM) devices
operated in binary mode to implement synapses in a convolutional neural network (CNN) is …
operated in binary mode to implement synapses in a convolutional neural network (CNN) is …
Dual functionality of threshold and multilevel resistive switching characteristics in nanoscale HfO2-based RRAM devices for artificial neuron and synapse elements
We demonstrate the dependency of dual functionality on the operating current with threshold
and multilevel switching behaviors in HfO 2-based resistive memory (RRAM) devices. These …
and multilevel switching behaviors in HfO 2-based resistive memory (RRAM) devices. These …
Filamentary TaOx/HfO2 ReRAM Devices for Neural Networks Training with Analog In‐Memory Computing
T Stecconi, R Guido, L Berchialla… - Advanced electronic …, 2022 - Wiley Online Library
The in‐memory computing paradigm aims at overcoming the intrinsic inefficiencies of Von‐
Neumann computers by reducing the data‐transport per arithmetic operation. Crossbar …
Neumann computers by reducing the data‐transport per arithmetic operation. Crossbar …
Impact of Post-Oxide Deposition Annealing on Resistive Switching in HfO2-Based Oxide RRAM and Conductive-Bridge RAM Devices
TL Tsai, HY Chang, FS Jiang… - IEEE Electron Device …, 2015 - ieeexplore.ieee.org
In this letter, we report the impact of post-oxide deposition annealing on the performance of
HfO 2-based resistive random access memory (RRAM) devices, namely, oxygen-ion-based …
HfO 2-based resistive random access memory (RRAM) devices, namely, oxygen-ion-based …
[HTML][HTML] Multilevel HfO2-based RRAM devices for low-power neuromorphic networks
Training and recognition with neural networks generally require high throughput, high
energy efficiency, and scalable circuits to enable artificial intelligence tasks to be operated at …
energy efficiency, and scalable circuits to enable artificial intelligence tasks to be operated at …
Optimized Programming Scheme Enabling Linear Potentiation in Filamentary HfO2 RRAM Synapse for Neuromorphic Systems
In this brief, we demonstrate the multilevel cell (MLC) characteristics of an HfO 2-based
resistive memory (RRAM) array as a synaptic element for neuromorphic systems. We utilize …
resistive memory (RRAM) array as a synaptic element for neuromorphic systems. We utilize …
HfO2-based resistive switching memory devices for neuromorphic computing
HfO 2-based resistive switching memory (RRAM) combines several outstanding properties,
such as high scalability, fast switching speed, low power, compatibility with complementary …
such as high scalability, fast switching speed, low power, compatibility with complementary …
Variability-tolerant convolutional neural network for pattern recognition applications based on OxRAM synapses
Software implementations of artificial Convolutional Neural Networks (CNNs), taking
inspiration from biology, are at the state-of-the-art for Pattern Recognition (PR) applications …
inspiration from biology, are at the state-of-the-art for Pattern Recognition (PR) applications …
Oxide-based RRAM materials for neuromorphic computing
XL Hong, DJJ Loy, PA Dananjaya, F Tan… - Journal of materials …, 2018 - Springer
In this review, a comprehensive survey of different oxide-based resistive random-access
memories (RRAMs) for neuromorphic computing is provided. We begin with the history of …
memories (RRAMs) for neuromorphic computing is provided. We begin with the history of …
Linking conductive filament properties and evolution to synaptic behavior of RRAM devices for neuromorphic applications
We perform a comparative study of HfO 2 and Ta 2 O 5 resistive switching memory (RRAM)
devices for their possible application as electronic synapses. By means of electrical …
devices for their possible application as electronic synapses. By means of electrical …