Results 11 to 20 of about 7,322 (252)

The Intel neuromorphic DNS challenge

Neuromorphic Computing and Engineering, 2023
A critical enabler for progress in neuromorphic computing research is the ability to transparently evaluate different neuromorphic solutions on important tasks and to compare them to state-of-the-art conventional solutions.
Jonathan Timcheck, Sumit Bam Shrestha, Daniel Ben Dayan Rubin, Adam Kupryjanow, Garrick Orchard, Lukasz Pindor, Timothy Shea, Mike Davies   +7 more
doaj   +1 more source

Neuromorphic quantum computing

Physical Review E, 2022
9 pages, 8 ...
Pehle, Christian, Wetterich, Christof
openaire   +3 more sources

Simulation-based inference for model parameterization on analog neuromorphic hardware

Neuromorphic Computing and Engineering, 2023
The BrainScaleS-2 (BSS-2) system implements physical models of neurons as well as synapses and aims for an energy-efficient and fast emulation of biological neurons.
Jakob Kaiser, Raphael Stock, Eric Müller, Johannes Schemmel, Sebastian Schmitt   +4 more
doaj   +1 more source

CMOS-compatible neuromorphic devices for neuromorphic perception and computing: a review

International Journal of Extreme Manufacturing, 2023
Neuromorphic computing is a brain-inspired computing paradigm that aims to construct efficient, low-power, and adaptive computing systems by emulating the information processing mechanisms of biological neural systems.
Yixin Zhu, Huiwu Mao, Ying Zhu, Xiangjing Wang, Chuanyu Fu, Shuo Ke, Changjin Wan, Qing Wan   +7 more
doaj   +1 more source

Recent Progress of Optoelectronic and All‐Optical Neuromorphic Devices: A Comprehensive Review of Device Structures, Materials, and Applications

Advanced Intelligent Systems, 2021
Conventional von Neumann–based computing systems have inherent limitations such as high hardware complexity, relatively inferior energy efficiency, and low bandwidth.
Seungho Song, Jeehoon Kim, Sung Min Kwon, Jeong‐Wan Jo, Sung Kyu Park, Yong‐Hoon Kim   +5 more
doaj   +1 more source

Editorial: Focus on algorithms for neuromorphic computing

Neuromorphic Computing and Engineering, 2023
Neuromorphic computing provides a promising energy-efficient alternative to von-Neumann-type computing and learning architectures. However, the best neuromorphic hardware is useless without suitable inference and learning algorithms that can fully ...
Robert Legenstein, Arindam Basu, Priyadarshini Panda   +2 more
doaj   +1 more source

Neuromorphic Computing

Elements, 2022
In the face of increasingly large computational demands and the impending halt to Moore's law, the semiconductor industry has been forced to re-evaluate the traditional computing paradism. Central to this re-evaluation has been the novel development of neuromorphic computing - an approach that, at its core, seeks to replicate the brain in silicon ...
null Elements, Will Riherd
openaire   +1 more source

Low-Power Memristor for Neuromorphic Computing: From Materials to Applications [PDF]

Nano-Micro Letters
Jia-Lin Meng, Tian-Yu Wang
exaly   +2 more sources

A neuromorphic approach to computer vision [PDF]

Communications of the ACM, 2010
Neuroscience is beginning to inspire a new generation of seeing machines.
Serre, Thomas, Poggio, Tomaso A.
openaire   +3 more sources

Emerging Opportunities for 2D Materials in Neuromorphic Computing

Nanomaterials, 2023
Recently, two-dimensional (2D) materials and their heterostructures have been recognized as the foundation for future brain-like neuromorphic computing devices.
Chenyin Feng, Wenwei Wu, Huidi Liu, Junke Wang, Houzhao Wan, Guokun Ma, Hao Wang   +6 more
doaj   +1 more source