Results 251 to 260 of about 95,522 (318)

ReRAM/CMOS Array Integration and Characterization via Design of Experiments

Advanced Electronic Materials, EarlyView.
This paper proposes the Design of Experiments to characterize arrays of oxide‐based ReRAM devices by exploring the large characterization space efficiently using only a few numbers of experiments. Using in‐house integration of 20 000 ReRAM devices on a CMOS chip, the unconventional optimization approach determines optimized measurement parameters and ...
Imtiaz Hossen, William A. Borders, Advait Madhavan, Shweta Joshi, Patrick M. Braganca, Jabez J. McClelland, Brian D. Hoskins, Gina C. Adam   +7 more
wiley   +1 more source

Memristor Synapse-A Device-Level Critical Review. [PDF]

Nanomaterials (Basel)
Chandrasekaran S, Chang YF, Simanjuntak FM.   +2 more
europepmc   +1 more source

Neural Information Processing and Time‐Series Prediction with Only Two Dynamical Memristors

Advanced Electronic Materials, EarlyView.
The present study demonstrates how simple circuits with only two memristive devices are utilized to perform high complexity temporal information processing tasks, like neural spike detection in noisy environment, or time‐series prediction. This circuit simplicity is enabled by the dynamical complexity of the memristive devices, i.e.
Dániel Molnár, Tímea Nóra Török, János Volk, Roland Kövecs, László Pósa, Péter Balázs, György Molnár, Nadia Jimenez Olalla, Zoltán Balogh, János Volk, Juerg Leuthold, Miklós Csontos, András Halbritter   +12 more
wiley   +1 more source

Multisensory Neuromorphic Devices: From Physics to Integration. [PDF]

Nanomicro Lett
Gui A, Mu H, Yang R, Zhang G, Lin S.
europepmc   +1 more source

Neuromorphic Motor Control with Electrolyte‐Gated Organic Synaptic Transistors

Advanced Electronic Materials, EarlyView.
Electrolyte‐gated organic synaptic transistor (EGOST)‐based neuromorphic motor control systems integrate sensing, processing, and actuation by mimicking biological synapses. With advantages such as low power consumption, tunable synaptic plasticity, and mechanical flexibility, they are emerging as next‐generation core technologies for real‐time ...
Sung‐Hwan Kim, Ju‐Hyeok Yun, Hea‐Lim Park, Sin‐Hyung Lee   +3 more
wiley   +1 more source

NeoHebbian synapses to accelerate online training of neuromorphic hardware. [PDF]

Sci Rep
Pande S, Bezugam SS, Bhattacharya T, Wlazlak E, Chakravorty A, Chakrabarti B, Strukov D.   +6 more
europepmc   +1 more source

Synaptic behavior in dye-sensitized solar cell-based optoelectronic artificial synaptic devices towards self-powered physical reservoir computing

Norika Hosoda, Hiroaki Komatsu, Takashi Ikuno   +2 more
openalex   +1 more source

Metaplastic synaptic behaviour operational in FM devices

The dependence of the switching probability on the MI state of the gate will be evaluated for each of the proposed schemes [UPSaclay, CEITEC]. The device design will be adapted based on the most performing dependences used in metaplastic algorithms and based on biological neural models [UPSaclay, FZJ, UZH, HawAI.tech].
openaire   +1 more source

Optical Charge Trap Memory Based on Graphene/ZnO Heterostructures for Long‐Term Retention and Adaptive Learning

Advanced Electronic Materials, EarlyView.
A biocompatible graphene/ZnO optical charge trap memory (CTM) is reported with over 54 h retention, enabled by interfacial photodoping. Using transient absorption spectroscopy and electrical analysis, charge transfer quenching is elucidated and reveal that a large energy barrier at the interface is responsible for long‐term memory retention.
Seungmin Shin, Junhyung Kim, Hyungdoh Lee, Yixuan Dou, Jacob T. Heiden, Seung Eun Lee, Jinwoo Song, Lina Quan, Giulia Tagliabue, Min Seok Jang, Himchan Cho   +10 more
wiley   +1 more source

Overcoming Volatility in Ion Gel via Ag Doping for Nonvolatile Memristive Switching. [PDF]

ACS Omega
Nam J, Jeong J, Lee S, Kim Y, Jeon W.
europepmc   +1 more source