Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Mark Edward Dean"'
Publikováno v:
IEEE Access, Vol 7, Pp 135606-135620 (2019)
Multiple neuromorphic systems use spiking neural networks (SNNs) to perform computation in a way that is inspired by concepts learned about the human brain. SNNs are artificial networks made up of neurons that fire a pulse, or spike, once the accumul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bf1a8a050f399cc384ef1177ad98e08
https://doi.org/10.1109/access.2019.2941772
https://doi.org/10.1109/access.2019.2941772
Autor:
Grant Bruer, James S. Plank, Mark Edward Dean, Adam Z. Foshie, Garrett S. Rose, Catherine D. Schuman, J. Parker Mitchell, Jonathan D. Ambrose
Publikováno v:
IJCNN
In this work we describe the design, implementation, and testing of the first neuromorphic robot capable of obstacle avoidance, grid coverage, and targeting controlled by the second generation Dynamic Adaptive Neural Network Array (DANNA2) digital sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56664224fcc347451b4eac26332b5838
https://doi.org/10.1109/ijcnn48605.2020.9207276
https://doi.org/10.1109/ijcnn48605.2020.9207276
Autor:
Aaron Young, Garrett S. Rose, James S. Plank, J. Parker Mitchell, Mark Edward Dean, Catherine D. Schuman, Adam Z. Foshie
Publikováno v:
IJCNN
Neuromorphic computing is one promising post-Moore’s law era technology, which takes inspiration from biological brains to perform computing tasks. The human brain contains billions of neurons with trillions of synapses and as neuromorphic hardware
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3e4d3bcf66f14f525c0f0a5e4181876
https://doi.org/10.1109/ijcnn48605.2020.9206920
https://doi.org/10.1109/ijcnn48605.2020.9206920
Publikováno v:
IEEE Letters of the Computer Society. 1:17-20
Spiking, neuromorphic computing systems are in a period of active exploration by the computing community. While they feature computational expressiveness beyond both von Neumann computing models and feed-forward neural networks, they are also challen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a868d495d6dcc158ca3bff027c607b5c
https://doi.org/10.1109/locs.2018.2885976
https://doi.org/10.1109/locs.2018.2885976
Publikováno v:
Proceedings of the International Conference on Neuromorphic Systems.
Following from the original Dynamic Adaptive Neural Network Array (DANNA) model, we propose a new digital neuromorphic architecture named DANNA 2. Through this paper, we introduce our new hardware design and software simulator, and we explain how DAN
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41017bd1fa24c5e702b889da9902b2b5
https://doi.org/10.1145/3229884.3229894
https://doi.org/10.1145/3229884.3229894
Autor:
Grant Bruer, James S. Plank, Adam Disney, Garrett S. Rose, John V. Reynolds, Catherine D. Schuman, Mark Edward Dean
Publikováno v:
Proceedings of the International Conference on Neuromorphic Systems.
A variety of neural network models and machine learning techniques have arisen over the past decade, and their successes with image classification have been stunning. With other classification tasks, selecting and configuring a neural network solutio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b12cbdcab4b77cdb6fe4a2d92615ffbf
https://doi.org/10.1145/3229884.3229896
https://doi.org/10.1145/3229884.3229896
Publikováno v:
Proceedings of the International Conference on Neuromorphic Systems.
DANNA is a computing architecture, designed in 2014 to meld features of recurrent, spiking, plastic neuromorphic computing systems with very efficient hardware implementations. Its hardware design and FPGA implementation preceded any software support
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d9145390d1e2c9fffab223dc56f70b6d
https://doi.org/10.1145/3229884.3229893
https://doi.org/10.1145/3229884.3229893
Publikováno v:
IJCNN
Evolutionary optimization or genetic algorithms have been used to optimize a variety of neural network types, including spiking recurrent neural networks, and are attractive for many reasons. However, a key impediment to their widespread use is the p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d861354d6446754626183789bb86cb9
https://doi.org/10.1109/ijcnn.2018.8489149
https://doi.org/10.1109/ijcnn.2018.8489149
Publikováno v:
IJCNN
Neuromorphic computing is one promising post-Moore’s law era technology. In order to develop and use neuromorphic systems, traditional von Neumann-based computers must be able to communicate with neuromorphic hardware to support functionality such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddaa01d67221c37e3ab6630a3db19ff8
https://doi.org/10.1109/ijcnn.2018.8489694
https://doi.org/10.1109/ijcnn.2018.8489694
Autor:
Nicholas D. Skuda, Mark Edward Dean, Gangotree Chakma, Garrett S. Rose, Catherine D. Schuman, James S. Plank
Publikováno v:
ACM Great Lakes Symposium on VLSI
Resource constrained devices are the building blocks of the internet of things (IoT) era. Since the idea behind IoT is to develop an interconnected environment where the devices are tiny enough to operate with limited resources, several control syste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c40030ad12ed7656a066a2b487bbcf99
https://doi.org/10.1145/3194554.3194611
https://doi.org/10.1145/3194554.3194611