Results 71 to 80 of about 37,924 (271)

Universal Neuromorphic Element: NbOx Memristor with Co‐Existing Volatile, Non‐Volatile, and Threshold Switching

Advanced Functional Materials, EarlyView.
A W/NbOx/Pt memristor demonstrates the coexistence of volatile, non‐volatile, and threshold switching characteristics. Volatile switching serves as a reservoir computing layer, providing dynamic short‐term processing. Non‐volatile switching, stabilized through ISPVA, improves reliable long‐term readout. Threshold switching operates as a leaky integrate
Ungbin Byun, Hyesung Na, Sungjun Kim
wiley   +1 more source

Perception Understanding Action: Adding Understanding to the Perception Action Cycle With Spiking Segmentation

Frontiers in Neurorobotics, 2020
Traditionally the Perception Action cycle is the first stage of building an autonomous robotic system and a practical way to implement a low latency reactive system within a low Size, Weight and Power (SWaP) package.
Paul Kirkland, Gaetano Di Caterina, John Soraghan, George Matich   +3 more
doaj   +1 more source

Training and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors

, 2014
Despite all the progress of semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging.
Adam, Gina, Hoskins, Brian, Likharev, Konstantin K., Merrikh-Bayat, Farnood, Prezioso, Mirko, Strukov, Dmitri B.   +5 more
core   +1 more source

A Van der Waals Optoelectronic Synapse with Tunable Positive and Negative Post‐Synaptic Current for Highly Accurate Spiking Neural Networks

Advanced Functional Materials, EarlyView.
A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon, Soeun Park, Yeong Kwon Kim, Juhwan Baek, Ki Han Kim, Seongil Yun, Hyeonchang Son, Jeongeun Choi, Byung Chul Jang, Dong‐Ho Kang   +9 more
wiley   +1 more source

Perspective: Organic electronic materials and devices for neuromorphic engineering

, 2018
Neuromorphic computing and engineering has been the focus of intense research efforts that have been intensified recently by the mutation of Information and Communication Technologies (ICT). In fact, new computing solutions and new hardware platforms are
Alibart, Fabien, Pecqueur, Sebastien, Vuillaume, Dominique   +2 more
core   +2 more sources

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Consciousness Detection in a Complete Locked-in Syndrome Patient through Multiscale Approach Analysis

Entropy, 2020
Completely locked-in state (CLIS) patients are unable to speak and have lost all muscle movement. From the external view, the internal brain activity of such patients cannot be easily perceived, but CLIS patients are considered to still be conscious and ...
Shang-Ju Wu, Nicoletta Nicolaou, Martin Bogdan   +2 more
doaj   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Stochastic rounding for memory-efficient digital simulation of synaptic plasticity using 8-bit floating-point

Neuromorphic Computing and Engineering
Simulating brain-scale networks digitally is often hindered by extensive memory access. In this context, using low-precision data types and more efficient models to represent state variables is a viable alternative to improve the scalability of the ...
Pablo Urbizagastegui, André van Schaik, Runchun Wang   +2 more
doaj   +1 more source

A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines

, 2017
Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural networks is the vector-matrix multiply when inputs are multiplied by the neural ...
Aimone, James B., Carlson, Kristofor D., Donaldson, Jonathon, Follett, David R., Follett, Pamela L., Hill, Aaron J., James, Conrad D., Naegle, John H., Smith, Michael R., Vineyard, Craig M.   +9 more
core   +1 more source