Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Emre Neftci"'
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
Neuromorphic cognitive computing offers a bio-inspired means to approach the natural intelligence of biological neural systems in silicon integrated circuits. Typically, such circuits either reproduce biophysical neuronal dynamics in great detail as
Externí odkaz:
https://doaj.org/article/3b6f5474c7ee4bbe90a9224397903855
Autor:
Sourav Dutta, Georgios Detorakis, Abhishek Khanna, Benjamin Grisafe, Emre Neftci, Suman Datta
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-10 (2022)
Neural sampling machines make use of noise to perform learning. Here, Dutta et al. present a hybrid stochastic synapse composed out of a ferroelectric transistor combined with a stochastic selector exhibiting multiplicative synaptic noise required fo
Externí odkaz:
https://doaj.org/article/d5979bc727ec411d92d5e742328b3579
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Externí odkaz:
https://doaj.org/article/219cbf56f2704e138548055443b4d32b
Publikováno v:
Neuromorphic Computing and Engineering, Vol 3, Iss 3, p 030403 (2023)
Externí odkaz:
https://doaj.org/article/84a5a612f0634dc6a1124e20b8c293a7
Publikováno v:
Frontiers in Neuroscience, Vol 14 (2020)
A growing body of work underlines striking similarities between biological neural networks and recurrent, binary neural networks. A relatively smaller body of work, however, addresses the similarities between learning dynamics employed in deep artifi
Externí odkaz:
https://doaj.org/article/6dc29d8416594e7eb09e3a43cb3713ce
Autor:
Georgios Detorakis, Sadique Sheik, Charles Augustine, Somnath Paul, Bruno U. Pedroni, Nikil Dutt, Jeffrey Krichmar, Gert Cauwenberghs, Emre Neftci
Publikováno v:
Frontiers in Neuroscience, Vol 12 (2018)
Embedded, continual learning for autonomous and adaptive behavior is a key application of neuromorphic hardware. However, neuromorphic implementations of embedded learning at large scales that are both flexible and efficient have been hindered by a l
Externí odkaz:
https://doaj.org/article/b53ac9498a37489dbecdfc3023df49cd
Publikováno v:
AIP Advances, Vol 6, Iss 11, Pp 111304-111304-7 (2016)
In neuromorphic circuits, stochasticity in the cortex can be mapped into the synaptic or neuronal components. The hardware emulation of these stochastic neural networks are currently being extensively studied using resistive memories or memristors
Externí odkaz:
https://doaj.org/article/962b02abffac45a99339e7548b1b34f7
Publikováno v:
PLoS Computational Biology, Vol 11, Iss 11, p e1004592 (2015)
We often learn and recall long sequences in smaller segments, such as a phone number 858 534 22 30 memorized as four segments. Behavioral experiments suggest that humans and some animals employ this strategy of breaking down cognitive or behavioral s
Externí odkaz:
https://doaj.org/article/f98b15b430fb4cc29b627ef4fdb5c5cd
Publikováno v:
Neural Networks. 161:228-241
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12f942486252e181b55233a333f5a922
https://doi.org/10.1016/j.neunet.2023.01.025
https://doi.org/10.1016/j.neunet.2023.01.025
Publikováno v:
Proceedings of the Neuromorphic Materials, Devices, Circuits and Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2eb6b6c91c5e15d09a86d2ccd3ecabce
https://doi.org/10.29363/nanoge.neumatdecas.2023.043
https://doi.org/10.29363/nanoge.neumatdecas.2023.043