Zobrazeno 1 - 10
of 84
pro vyhledávání: '"analog hardware"'
Publikováno v:
IEEE Access, Vol 12, Pp 116226-116237 (2024)
Probability estimation measures the likelihood of different outcomes in a statistical context. It commonly involves estimating either the parameters or the entire distribution of a random variable. Parametric approaches, where a specific functional f
Externí odkaz:
https://doaj.org/article/acff69297ef44a0da50eb53cef7c566d
Autor:
Vassilis Alimisis, Dimitrios G. Arnaoutoglou, Emmanouil Anastasios Serlis, Argyro Kamperi, Konstantinos Metaxas, George A. Kyriacou, Paul P. Sotiriadis
Publikováno v:
IEEE Open Journal of Circuits and Systems, Vol 5, Pp 224-242 (2024)
A fall-detection system was implemented utilizing a 2.45 GHz continuous wave radar along with power-efficient and fully-analog integrated classifier architectures. The Power Burst Curve and the effective acceleration were derived from the short time
Externí odkaz:
https://doaj.org/article/f0fcf29ab16f4a3b98e9e395031bfb76
Autor:
Fabia Farlin Athena, Omobayode Fagbohungbe, Nanbo Gong, Malte J. Rasch, Jimmy Penaloza, SoonCheon Seo, Arthur Gasasira, Paul Solomon, Valeria Bragaglia, Steven Consiglio, Hisashi Higuchi, Chanro Park, Kevin Brew, Paul Jamison, Christopher Catano, Iqbal Saraf, Claire Silvestre, Xuefeng Liu, Babar Khan, Nikhil Jain, Steven McDermott, Rick Johnson, I. Estrada-Raygoza, Juntao Li, Tayfun Gokmen, Ning Li, Ruturaj Pujari, Fabio Carta, Hiroyuki Miyazoe, Martin M. Frank, Antonio La Porta, Devi Koty, Qingyun Yang, Robert D. Clark, Kandabara Tapily, Cory Wajda, Aelan Mosden, Jeff Shearer, Andrew Metz, Sean Teehan, Nicole Saulnier, Bert Offrein, Takaaki Tsunomura, Gert Leusink, Vijay Narayanan, Takashi Ando
Publikováno v:
Frontiers in Electronics, Vol 4 (2024)
Analog memory presents a promising solution in the face of the growing demand for energy-efficient artificial intelligence (AI) at the edge. In this study, we demonstrate efficient deep neural network transfer learning utilizing hardware and algorith
Externí odkaz:
https://doaj.org/article/251ccb96d4dd435e83908250513bf0fa
Publikováno v:
Sensors, Vol 23, Iss 8, p 3978 (2023)
A novel analog integrated implementation of a hardware-friendly support vector machine algorithm that can be a part of a classification system is presented in this work. The utilized architecture is capable of on-chip learning, making the overall cir
Externí odkaz:
https://doaj.org/article/082179c8f1434586ac39d062761f0f63
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2019, Iss 1, Pp 1-11 (2019)
Abstract This work proposes an analog implementation of gradient-based algorithm for compressive sensing signal reconstruction. Compressive sensing has appeared as a promising technique for efficient acquisition and reconstruction of sparse signals i
Externí odkaz:
https://doaj.org/article/ec2d9c5adbe64e68b8d40de298408d46
Autor:
Tayfun Gokmen, Wilfried Haensch
Publikováno v:
Frontiers in Neuroscience, Vol 14 (2020)
Hardware architectures composed of resistive cross-point device arrays can provide significant power and speed benefits for deep neural network training workloads using stochastic gradient descent (SGD) and backpropagation (BP) algorithm. The trainin
Externí odkaz:
https://doaj.org/article/aa41a56889bd4b57b28303e973cb9fc6
Akademický článek
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Akademický článek
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Publikováno v:
Frontiers in Neuroscience, Vol 12 (2018)
In our previous work we have shown that resistive cross point devices, so called resistive processing unit (RPU) devices, can provide significant power and speed benefits when training deep fully connected networks as well as convolutional neural net
Externí odkaz:
https://doaj.org/article/fadca02a41a74dd692acdf874c23c4eb
Autor:
Persson, Ludwig, Uusitalo, Laura
Despite software being commonplace in the recording industry today, preconceptions exist regarding the digital equivalents of yesteryears hardware. Whilst studies within the field of cognitive psychology shows that prejudice can influence sense-exper
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-219740
