Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Walt Woods"'
Autor:
Sam Lilak, Walt Woods, Kelsey Scharnhorst, Christopher Dunham, Christof Teuscher, Adam Z. Stieg, James K. Gimzewski
Publikováno v:
Frontiers in Nanotechnology, Vol 3 (2021)
Atomic Switch Networks comprising silver iodide (AgI) junctions, a material previously unexplored as functional memristive elements within highly interconnected nanowire networks, were employed as a neuromorphic substrate for physical Reservoir Compu
Externí odkaz:
https://doaj.org/article/da44452925ee4988bd0719d1c924d33f
Autor:
Marek Osinski, Mark Wetzel, Sebastian Reynolds, Adam J. Morton, Merlin Carson, Christof Teuscher, Walt Woods, A. A. Hecht
Publikováno v:
IEEE Transactions on Nuclear Science. 68:292-304
Many radionuclide identification algorithms use statistical inference to collect a variety of features from gamma-ray spectra to deduce the presence of particular radionuclides. More modern algorithms require large amounts of data to learn and use la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fda219afda7a6ca961ad0254fbc5dd8b
https://doi.org/10.1109/tns.2021.3054608
https://doi.org/10.1109/tns.2021.3054608
Autor:
Walt Woods, Christof Teuscher
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 30:2173-2187
Memristive crossbars have become a popular means for realizing unsupervised and supervised learning techniques. In previous neuromorphic architectures with leaky integrate-and-fire neurons, the crossbar itself has been separated from the neuron capac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6cf6de9f108932e9fb9de059e1df24a9
https://doi.org/10.1109/tnnls.2018.2878002
https://doi.org/10.1109/tnnls.2018.2878002
Autor:
Walt Woods
Publikováno v:
SP Workshops
When working to understand usage of a data format, examples of the data format are often more representative than the format's specification. For example, two different applications might use very different JSON representations, or two PDF-writing ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d69fb7985fbab73290e20b2647c51d8f
Publikováno v:
ISCAS
Memristor arrays are promising structures for energy-efficient neuromorphic computing systems. However, due to their nondeterministic fabrication process, manufacturing defects can degrade computation accuracy. In this paper, a memristor-based neurom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70404c4b0dbde84ef497f20ff3846f80
https://doi.org/10.1109/iscas45731.2020.9180669
https://doi.org/10.1109/iscas45731.2020.9180669
For sensitive problems, such as medical imaging or fraud detection, Neural Network (NN) adoption has been slow due to concerns about their reliability, leading to a number of algorithms for explaining their decisions. NNs have also been found vulnera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::314e1ee1ee7c69e0a31db140cb2064c5
http://arxiv.org/abs/1906.02896
http://arxiv.org/abs/1906.02896
Publikováno v:
IEEE Transactions on Nanotechnology. 14:945-953
Memristors promise a means for high-density neuromorphic nanoscale architectures that leverage in situ learning algorithms. While traditional learning algorithms commonly assume analog values for synaptic weights, actual physical memristors may have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c0d0a5b548ed11cec7c53a2ab2a5476
https://doi.org/10.1109/tnano.2015.2449835
https://doi.org/10.1109/tnano.2015.2449835
Publikováno v:
NANOARCH
Efforts to achieve a low-power, dynamically complex system become crucial as CMOS fabrication limits are realized. Atomic Switch Networks (ASNs) provide fabrication advantages over traditional CMOS through the combination of top-down and bottom-up te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd9fa1ca668187c96f2af1ad42e49136
https://doi.org/10.1109/nanoarch.2017.8053728
https://doi.org/10.1109/nanoarch.2017.8053728
Autor:
Christof Teuscher, Walt Woods
Publikováno v:
NANOARCH
Modern neuromorphic deep learning techniques, as well as unsupervised techniques like the locally competitive algorithm, rely on Vector Matrix Multiplications (VMMs). When designing biologically-inspired circuits, a VMM is used to represent synapse w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9e4d17fc78bd95a06a57249389620ba
https://doi.org/10.1109/nanoarch.2017.8053729
https://doi.org/10.1109/nanoarch.2017.8053729
Publikováno v:
NANOARCH
The popularity of memristors has led to a wide range of models being proposed for both physically realized devices and their concepts in general. These models have been fit to specific devices, but the resulting device models are not often discussed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d39f93139682e19ec66ec53a4cf79065
https://doi.org/10.1109/nanoarch.2015.7180595
https://doi.org/10.1109/nanoarch.2015.7180595