Results 81 to 90 of about 14,261 (179)

NeuroPong: the event-based camera driven embedded neuromorphic system

Neuromorphic Computing and Engineering
Neuromorphic computing is a novel style of computing that features low-power spiking neural networks (SNNs) as the main compute components. It is an event-driven computational paradigm that naturally pairs with event-based cameras and their asynchronous ...
Charles P Rizzo, Bryson Gullett, Alex M Crumley, Maxwell E Marcum, Mason R Hyman, Carter Earheart-Brown, Julia Steed, Frank Standaert, Catherine D Schuman, James S Plank   +9 more
doaj   +1 more source

Design of Memristor Based Modified Synapse Circuit for Low-Power Neuromorphic Computing

Abstract It is high time that brain-inspired or neuromorphic computing must have enough concentration to grow and overcome the computational barrier, which will mimic the biological neuron cell, and its computational abilities will be applied from the neuroscience point of view.
Tarif Ahammad Fuad Hazari, A.B.M. Noushad Bhuiyan, Md. Israil Hossain   +2 more
openaire   +1 more source

Low‐Power Optoelectronic Synaptic Transistors with Multimodal Neuromorphic Computation and Retinal‐Inspired Multiband Optical Binary Communication

Small Science
Biomimetic neuromorphic optoelectronics exude tempting attraction in multimodal interaction and visual applications because of their capability of integrating sensing, memorizing, and processing in a single device. Herein, a natural dextran film that is intrinsically green and transparent is employed as the dielectric of the optoelectronic synaptic ...
Bo Huang, Linfeng Lan, Jiayi Pan, Fuzheng Qi, Jing Li, Churou Wang, Yaping Li, Dechun Zeng, Jiale Huang, Jintao Xu, Junbiao Peng   +10 more
openaire   +3 more sources

Stretchable neuromorphic electronics for future human-integrated intelligence

International Journal of Extreme Manufacturing
Neuromorphic electronics emulate the computational principles of biological neural systems, offering low-power, adaptive, and parallel signal processing capabilities for next-generation intelligent systems.
Tianda Fu, Ruizhe Yang, Max Weires, Junyi Yin, Yifan Liao, Yifan Guo   +5 more
doaj   +1 more source

2D Spintronics for Neuromorphic Computing with Scalability and Energy Efficiency

Journal of Low Power Electronics and Applications
The demand for computing power has been growing exponentially with the rise of artificial intelligence (AI), machine learning, and the Internet of Things (IoT).
Douglas Z. Plummer, Emily D’Alessandro, Aidan Burrowes, Joshua Fleischer, Alexander M. Heard, Yingying Wu   +5 more
doaj   +1 more source

Enhanced Linear Conductance Modulation by La‐Doping in HfO2‐Based Memristors for Neuromorphic Applications

Advanced Electronic Materials
Efficient computing systems require low‐power and high‐density memory technologies capable of supporting advanced applications such as neuromorphic computing and artificial intelligence. Hafnium oxide (HfO2) based resistive random‐access memory (RRAM) is
Taewook Kim, Márton Major, Enrique Miranda, Philipp Schreyer, Yingxin Li, Yu Duan, Alexey Arzumanov, Tobias Vogel, Nico Kaiser, Eszter Piros, Lambert Alff   +10 more
doaj   +1 more source

Neuromorphic Computing for IoT: Ultra-Low Power AI for Real-Time Intelligence

International Journal For Multidisciplinary Research
Neuromorphic computing presents a promising approach for enabling artificial intelligence capabilities in Internet of Things (IoT) devices with stringent power constraints. This paper explores the potential of neuromorphic architectures to deliver ultra-low power AI for real-time intelligence in IoT applications.
openaire   +1 more source

The backpropagation algorithm implemented on spiking neuromorphic hardware

Nature Communications
The capabilities of natural neural systems have inspired both new generations of machine learning algorithms as well as neuromorphic, very large-scale integrated circuits capable of fast, low-power information processing. However, it has been argued that
Alpha Renner, Forrest Sheldon, Anatoly Zlotnik, Louis Tao, Andrew Sornborger   +4 more
doaj   +1 more source

Optimization strategy of the emerging memristors: From material preparation to device applications

iScience
Summary: With the advent of the post-Moore era and the era of big data, advanced data storage and processing technology are in urgent demand to break the von Neumann bottleneck.
Kaiyun Gou, Yanran Li, Honglin Song, Rong Lu, Jie Jiang   +4 more
doaj   +1 more source

Multi-level, forming and filament free, bulk switching trilayer RRAM for neuromorphic computing at the edge

Nature Communications
CMOS-RRAM integration holds great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from variations and noise, leading to computational accuracy loss, increased ...
Jaeseoung Park, Ashwani Kumar, Yucheng Zhou, Sangheon Oh, Jeong-Hoon Kim, Yuhan Shi, Soumil Jain, Gopabandhu Hota, Erbin Qiu, Amelie L. Nagle, Ivan K. Schuller, Catherine D. Schuman, Gert Cauwenberghs, Duygu Kuzum   +13 more
doaj   +1 more source