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pro vyhledávání: '"Singh, Ojasvi"'
Exploring Column Update Elimination Optimization for Spike-Timing-Dependent Plasticity Learning Rule
Autor:
Singh, Ojasvi
Hebbian learning based neural network learning rules when implemented on hardware, store their synaptic weights in the form of a two-dimensional matrix. The storage of synaptic weights demands large memory bandwidth and storage. While memory units ar
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-309354
Publikováno v:
In Materials Today: Proceedings 2017 4(8):8409-8417
Publikováno v:
In Materials Today: Proceedings 2015 2(4-5):2407-2413
Autor:
Singh, Ojasvi
Hebbian learning based neural network learning rules when implemented on hardware, store their synaptic weights in the form of a two-dimensional matrix. The storage of synaptic weights demands large memory bandwidth and storage. While memory units ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::178b991ddf7b000e8e65448e3e262fe2
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-309354
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-309354