Results 211 to 220 of about 7,731 (250)

The neurobench framework for benchmarking neuromorphic computing algorithms and systems. [PDF]

Nat Commun
Yik J, Van den Berghe K, den Blanken D, Bouhadjar Y, Fabre M, Hueber P, Ke W, Khoei MA, Kleyko D, Pacik-Nelson N, Pierro A, Stratmann P, Sun PV, Tang G, Wang S, Zhou B, Ahmed SH, Vathakkattil Joseph G, Leto B, Micheli A, Mishra AK, Lenz G, Sun T, Ahmed Z, Akl M, Anderson B, Andreou AG, Bartolozzi C, Basu A, Bogdan P, Bohte S, Buckley S, Cauwenberghs G, Chicca E, Corradi F, de Croon G, Danielescu A, Daram A, Davies M, Demirag Y, Eshraghian J, Fischer T, Forest J, Fra V, Furber S, Furlong PM, Gilpin W, Gilra A, Gonzalez HA, Indiveri G, Joshi S, Karia V, Khacef L, Knight JC, Kriener L, Kubendran R, Kudithipudi D, Liu SC, Liu YH, Ma H, Manohar R, Margarit-Taulé JM, Mayr C, Michmizos K, Muir DR, Neftci E, Nowotny T, Ottati F, Ozcelikkale A, Panda P, Park J, Payvand M, Pehle C, Petrovici MA, Posch C, Renner A, Sandamirskaya Y, Schaefer CJS, van Schaik A, Schemmel J, Schmidgall S, Schuman C, Seo JS, Sheik S, Shrestha SB, Sifalakis M, Sironi A, Stewart K, Stewart M, Stewart TC, Timcheck J, Tömen N, Urgese G, Verhelst M, Vineyard CM, Vogginger B, Yousefzadeh A, Zohora FT, Frenkel C, Reddi VJ.   +99 more
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An Energy Efficient Memory Cell for Quantum and Neuromorphic Computing at Low Temperatures. [PDF]

Nano Lett
Han Y, Sun J, Richstein B, Grenmyr A, Bae JH, Allibert F, Radu I, Grützmacher D, Knoch J, Zhao QT.   +9 more
europepmc   +1 more source

Dual SOT Switching Modes in a Single Device Geometry for Neuromorphic Computing. [PDF]

Nano Lett
Ranjan A, Farooq T, Chi CC, Sung HY, Salinas Padilla RI, Lin PH, Wu WW, Lu MY, Mishra R, Lai CH.   +9 more
europepmc   +1 more source

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Photonics for Neuromorphic Computing

2018 European Conference on Optical Communication (ECOC), 2018
An emerging field at the nexus of photonics/neuroscience, neuromorphic photonics combines the advantages of optics/electronics. In this tutorial, we will look at challenges of photonic information processing, describe photonic neural-network approaches, and offer a glimpse at this field's future.
Paul R. Prucnal, Alexander N. Tait, Mitchell A. Nahmias, Thomas Ferreira de Lima, Hsuan-Tung Peng, Bhavin J. Shastri   +5 more
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Memristor in neuromorphic computing

2012 IEEE International SOC Conference, 2012
As technology scaling down becomes more and more difficult, the traditional von Neumann computer architecture cannot satisfy people's unlimited demand on high performance computation. Consequently, the neuromorphic hardware systems providing the capabilities of biological perception and information processing at compact and energy-efficient platform ...
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Neuromorphic reservoir computing

Chaos: An Interdisciplinary Journal of Nonlinear Science
Reservoir computing has emerged as a promising machine-learning approach to prediction and control of complex nonlinear dynamical systems, rendering it important to explore schemes of physical realization. We articulate two frameworks of physical reservoir computing based on the electrophysiological mechanisms in mammalian neuronal networks.
Shirin Panahi, Zheng-Meng Zhai, Mulugeta Haile, Ying-Cheng Lai   +3 more
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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 computational systems, often for applications with size, weight and power constraints.
Dhireesha Kudithipudi, Catherine Schuman, Craig M. Vineyard, Tej Pandit, Cory Merkel, Rajkumar Kubendran, James B. Aimone, Garrick Orchard, Christian Mayr, Ryad Benosman, Joe Hays, Cliff Young, Chiara Bartolozzi, Amitava Majumdar, Suma George Cardwell, Melika Payvand, Sonia Buckley, Shruti Kulkarni, Hector A. Gonzalez, Gert Cauwenberghs, Chetan Singh Thakur, Anand Subramoney, Steve Furber   +22 more
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Matrix multiplication by neuromorphic computing

Neurocomputing, 2021
Abstract With increased requirements of processing power in many computing applications, and the consequent huge increases in resource costs including electrical power consumption, there is a push to find alternative computing architectures that achieve high speeds but require less resources.
Sheril Lawrence, Aishwarya Yandapalli, Shrisha Rao 0001   +2 more
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Insect-inspired neuromorphic computing

Current Opinion in Insect Science, 2018
The steady improvement in the performance of computing systems seen for many decades is levelling off as the miniaturization of semiconducting technology approaches the atomic limit, facing severe physical and technological issues. Neuromorphic computing is an emerging solution which makes use of silicon technology in a different way, inline with the ...
Dalgaty, Thomas, Vianello, Elisa, de Salvo, Barbara, Casas, Jérome   +3 more
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Synaptic electronics and neuromorphic computing

Science China Information Sciences, 2016
In order to map the computing architecture and intelligent functions of the human brain on hardware, we need electronic devices that can emulate biological synapses and even neurons, preferably at the physical level. Beginning with the history of neuromorphic computation, in this article, we will briefly review the architecture of the brain and the ...
Navnidhi K. Upadhyay, Saumil Joshi, J. Joshua Yang   +2 more
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