Results 41 to 50 of about 84,713 (260)

Synaptic metaplasticity with multi-level memristive devices

2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2023
Deep learning has made remarkable progress in various tasks, surpassing human performance in some cases. However, one drawback of neural networks is catastrophic forgetting, where a network trained on one task forgets the solution when learning a new one.
D’Agostino, S, Moro, F, Hirtzlin, T, Arcamone, J, Castellani, N, Querlioz, D, Payvand, Melika, Vianello, Elisa   +7 more
openaire   +3 more sources

Two‐Terminal MoS2‐Based Retinomorphic Devices with Enhanced Synaptic Plasticity

Advanced Electronic Materials
Neuromorphic visual systems mimicking biological retina functionalities are emerging as next‐generation retinomorphic devices for consolidating sensing and memorizing systems.
Younghoon Lim, Taehun Kim, Jaesik Eom, Onsik Harm, Junsung Byeon, Jungmoon Lim, Juwon Lee, Sangyeon Pak, SeungNam Cha   +8 more
doaj   +1 more source

Short-Term Plasticity and Long-Term Potentiation in Magnetic Tunnel Junctions: Towards Volatile Synapses

, 2016
Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally non-volatile long-term plasticity changes have been implemented in nanoelectronic synapses for neuromorphic applications, recent
Roy, Kaushik, Sengupta, Abhronil
core   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
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, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

An On-chip Trainable and Clock-less Spiking Neural Network with 1R Memristive Synapses

, 2017
Spiking neural networks (SNNs) are being explored in an attempt to mimic brain's capability to learn and recognize at low power. Crossbar architecture with highly scalable Resistive RAM or RRAM array serving as synaptic weights and neuronal drivers in ...
Ganguly, Udayan, Shukla, Aditya
core   +1 more source

Multicolor Optoelectronic Synapse Enabled by Photon‐Modulated Remote Doping in Solution‐Processed Van Der Waals Heterostructures

Advanced Functional Materials, EarlyView.
Multicolor optoelectronic synapses are realized by vertically integrating solution‐processed MoS2 thin‐film and SWCNT. The electronically disconnected but interactive MoS2 enables photon‐modulated remote doping, producing a bi‐directional photoresponse.
Jihyun Kim, Hyunbin Kim, Gang Jin Cheon, Dohyun Lee, In Soo Kim, Uiyeon Won, Jongseok Lee, Sang Min Won, Joohoon Kang   +8 more
wiley   +1 more source

A 3D Biofabricated Disease Model Mimicking the Brain Extracellular Matrix Suitable to Characterize Intrinsic Neuronal Network Alterations in the Presence of a Breast Tumor Disseminated to the Brain

Advanced Functional Materials, EarlyView.
A 3D disease model is developed using customized hyaluronic‐acid‐based hydrogels supplemented with extracellular matrix (ECM) proteins resembling brain ECM properties. Neurons, astrocytes, and tumor cells are used to mimic the native brain surrounding.
Esra Türker, Mateo S. Andrade Mier, Jessica Faber, Mike Friedrich, Zan Lamberger, Jeannette Weigelt, Christian Stigloher, Nicoletta Murenu, Natascha Schaefer, Jörg Tessmar, Gregor Lang, Silvia Budday, Katrin G. Heinze, Antje Appelt‐Menzel, Pamela L. Strissel, Reiner Strick, Carmen Villmann   +16 more
wiley   +1 more source

Long‐ and Short‐Term Memory Characteristics Controlled by Electrical and Optical Stimulations in InZnO‐Based Synaptic Device for Reservoir Computing

Advanced Electronic Materials
In this study, the resistive switching phenomenon and synaptic mimicry characteristics of an indium tin oxide (ITO)/indium zinc oxide (IZO)/Al2O3/TaN device are characterized.
Hyogeun Park, Dongyeol Ju, Chandreswar Mahata, Andrey Emelyanov, Minsuk Koo, Sungjun Kim   +5 more
doaj   +1 more source

Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array

Frontiers in Neuroscience, 2014
Recent advances in neuroscience together with nanoscale electronic device technology have resulted in huge interests in realizing brain-like computing hardwares using emerging nanoscale memory devices as synaptic elements.
Sukru Burc Eryilmaz, Duygu eKuzum, Rakesh eJeyasingh, SangBum eKim, Matthew eBrightSky, Chung eLam, H.-S. Philip eWong   +6 more
doaj   +1 more source

The Impact of On-chip Communication on Memory Technologies for Neuromorphic Systems

, 2018
Emergent nanoscale non-volatile memory technologies with high integration density offer a promising solution to overcome the scalability limitations of CMOS-based neural networks architectures, by efficiently exhibiting the key principle of neural ...
Manohar, Rajit, Moradi, Saber
core   +1 more source