Results 11 to 20 of about 1,614,108 (280)

Neuromorphic Computing [PDF]

International Journal on Advanced Computer Theory and Engineering
Basic games or tasks solved through Neuromorphic ...
Bikowski, Alex
core   +9 more sources

Neuromorphic Computing for Autonomous Racing

International Conference on Neuromorphic Systems 2021, 2021
Neuromorphic computing has many opportunities in future autonomous systems, especially those that will operate at the edge. However, there are relatively few demonstrations of neuromorphic implementations on real-world applications, partly because of the
Patton, Robert, Mitchell, J. P., Prasanna Date, Paulissen, Spencer, Potok, Thomas, Schuman, Catherine, J. Parker Mitchell, Catherine Schuman, Shruti Kulkarni, Spencer Paulissen, Christopher Stahl, Shay Snyder, Robert Patton, Sneider, Shay, Stahl, Christopher, Date, Prasanna, Thomas Potok, Haas, N. Q., Maryam Parsa, Kulkarni, Shruti, Parsa, Maryam, N. Quentin Haas   +21 more
core   +4 more sources

Generative Data for Neuromorphic Computing [PDF]

Proceedings of the Annual Hawaii International Conference on System Sciences
Neuromorphic computing is a next-generation model of computation that leverages biologically-inspired artificial neurons to perform complex tasks. Unlike neurons found within traditional Artificial Neural Networks (ANNs), which output on a continuous ...
Bihl, Trevor, Baietto, Anthony
core   +3 more sources

Neuromorphic computing at scale

Nature
Neuromorphic computing is a brain-inspired approach to hardware and algorithm design that efficiently realizes artificial neural networks. Neuromorphic designers apply the principles of biointelligence discovered by neuroscientists to design efficient ...
Majumdar, Amitava, Kubendran, Rajkumar, Bartolozzi, Chiara, Cardwell, Suma George, Gonzalez, Hector A., Hays, Joe, Aimone, James B., Subramoney, Anand, Schuman, Catherine, Buckley, Sonia, Furber, Steve, Mayr, Christian, Orchard, Garrick, Thakur, Chetan Singh, Benosman, Ryad, Pandit, Tej, Payvand, Melika, Merkel, Cory, Young, Cliff, Kudithipudi, Dhireesha, Kulkarni, Shruti, Cauwenberghs, Gert, Vineyard, Craig M.   +22 more
core   +3 more sources

Physics for neuromorphic computing [PDF]

Nature Reviews Physics, 2020
Neuromorphic computing takes inspiration from the brain to create energy efficient hardware for information processing, capable of highly sophisticated tasks. In this article, we make the case that building this new hardware necessitates reinventing electronics. We show that research in physics and material science will be key to create artificial nano-
Danijela Marković, Alice Mizrahi, Damien Querlioz, Julie Grollier   +3 more
openaire   +3 more sources

Two-Dimensional Oscillatory Neural Networks for Energy Efficient Neuromorphic Computing

, 2020
Neuro-inspired computing architectures are one of the leading candidates to solve complex and large-scale associative learning problems for AI applications. The two key building blocks for neuromorphic computing are the neuron and the synapse, which form
Linares-Barranco, Bernabé, Avedillo de Juan, María José, Hardelin, Tanguy, Abernot, Madeleine, Moselund, Kirsten, Karachristou, Eirini, Corti, Elisabetta, Gonos, Théophile, Karg, Siegfried, Rousseau, Matthieu, Carapezzi, Stefania, Boudaden, Jamila, Todri-Sanial, Aida, Gil, Thierry, Azemard, Nadine, Serrano-Gotarredona, Teresa, Núñez, Juan, Salles, Jérémie, Nejim, Ahmed, Klumpp, Armin   +19 more
core   +5 more sources

Neuromorphic quantum computing

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

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

Mechanical Properties Analysis of Flexible Memristors for Neuromorphic Computing [PDF]

Nano-Micro Letters
Jia-Lin Meng
exaly   +2 more sources