Zobrazeno 1 - 10
of 137
pro vyhledávání: '"Anthony J. Kenyon"'
Autor:
Adnan Mehonic, Daniele Ielmini, Kaushik Roy, Onur Mutlu, Shahar Kvatinsky, Teresa Serrano-Gotarredona, Bernabe Linares-Barranco, Sabina Spiga, Sergey Savel’ev, Alexander G. Balanov, Nitin Chawla, Giuseppe Desoli, Gerardo Malavena, Christian Monzio Compagnoni, Zhongrui Wang, J. Joshua Yang, Syed Ghazi Sarwat, Abu Sebastian, Thomas Mikolajick, Stefan Slesazeck, Beatriz Noheda, Bernard Dieny, Tuo-Hung (Alex) Hou, Akhil Varri, Frank Brückerhoff-Plückelmann, Wolfram Pernice, Xixiang Zhang, Sebastian Pazos, Mario Lanza, Stefan Wiefels, Regina Dittmann, Wing H. Ng, Mark Buckwell, Horatio R. J. Cox, Daniel J. Mannion, Anthony J. Kenyon, Yingming Lu, Yuchao Yang, Damien Querlioz, Louis Hutin, Elisa Vianello, Sayeed Shafayet Chowdhury, Piergiulio Mannocci, Yimao Cai, Zhong Sun, Giacomo Pedretti, John Paul Strachan, Dmitri Strukov, Manuel Le Gallo, Stefano Ambrogio, Ilia Valov, Rainer Waser
Publikováno v:
APL Materials, Vol 12, Iss 10, Pp 109201-109201-59 (2024)
Externí odkaz:
https://doaj.org/article/f5e2e018db184cdfa86a6be24ff6f6e6
Autor:
Dovydas Joksas, AbdulAziz AlMutairi, Oscar Lee, Murat Cubukcu, Antonio Lombardo, Hidekazu Kurebayashi, Anthony J. Kenyon, Adnan Mehonic
Publikováno v:
Advanced Intelligent Systems, Vol 4, Iss 8, Pp n/a-n/a (2022)
In a data‐driven economy, virtually all industries benefit from advances in information technology—powerful computing systems are critically important for rapid technological progress. However, this progress might be at risk of slowing down if th
Externí odkaz:
https://doaj.org/article/792ccf0ec26b4e41876fcc90bfab1db6
Autor:
Dovydas Joksas, Erwei Wang, Nikolaos Barmpatsalos, Wing H. Ng, Anthony J. Kenyon, George A. Constantinides, Adnan Mehonic
Publikováno v:
Advanced Science, Vol 9, Iss 17, Pp n/a-n/a (2022)
Abstract Recent years have seen a rapid rise of artificial neural networks being employed in a number of cognitive tasks. The ever‐increasing computing requirements of these structures have contributed to a desire for novel technologies and paradig
Externí odkaz:
https://doaj.org/article/0797a647837e4a4a9661556410e519cd
Autor:
Mark Buckwell, Wing H. Ng, Daniel J. Mannion, Horatio R. J. Cox, Stephen Hudziak, Adnan Mehonic, Anthony J. Kenyon
Publikováno v:
Frontiers in Nanotechnology, Vol 3 (2021)
Resistive random-access memories, also known as memristors, whose resistance can be modulated by the electrically driven formation and disruption of conductive filaments within an insulator, are promising candidates for neuromorphic applications due
Externí odkaz:
https://doaj.org/article/c1cdbdbe4c024d0bb9ea8fe7e774c965
Autor:
Horatio R. J. Cox, Mark Buckwell, Wing H. Ng, Daniel J. Mannion, Adnan Mehonic, Paul R. Shearing, Sarah Fearn, Anthony J. Kenyon
Publikováno v:
APL Materials, Vol 9, Iss 11, Pp 111109-111109-9 (2021)
The limited sensitivity of existing analysis techniques at the nanometer scale makes it challenging to systematically examine the complex interactions in redox-based resistive random access memory (ReRAM) devices. To test models of oxygen movement in
Externí odkaz:
https://doaj.org/article/6fb9ffa027bb410f95376d9d8dd875ab
Autor:
Adnan Mehonic, Abu Sebastian, Bipin Rajendran, Osvaldo Simeone, Eleni Vasilaki, Anthony J. Kenyon
Publikováno v:
Advanced Intelligent Systems, Vol 2, Iss 11, Pp n/a-n/a (2020)
Machine learning, particularly in the form of deep learning (DL), has driven most of the recent fundamental developments in artificial intelligence (AI). DL is based on computational models that are, to a certain extent, bio‐inspired, as they rely
Externí odkaz:
https://doaj.org/article/ebb5ac157c1c4f68ab829098c26feabf
Autor:
Mostafa Rahimi Azghadi, Ying-Chen Chen, Jason K. Eshraghian, Jia Chen, Chih-Yang Lin, Amirali Amirsoleimani, Adnan Mehonic, Anthony J. Kenyon, Burt Fowler, Jack C. Lee, Yao-Feng Chang
Publikováno v:
Advanced Intelligent Systems, Vol 2, Iss 5, Pp n/a-n/a (2020)
The ever‐increasing processing power demands of digital computers cannot continue to be fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing, which takes inspiration from the highly parallel, low‐power, hig
Externí odkaz:
https://doaj.org/article/205ef7b996874345886cf99c4dd1ebfd
Publikováno v:
Frontiers in Neuroscience, Vol 13 (2020)
Memristors have many uses in machine learning and neuromorphic hardware. From memory elements in dot product engines to replicating both synapse and neuron wall behaviors, the memristor has proved a versatile component. Here we demonstrate an analog
Externí odkaz:
https://doaj.org/article/addbbe27c6aa43079ee916df2605547c
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-8 (2018)
Abstract Inorganic semiconductors such as III-V materials are very important in our everyday life as they are used for manufacturing optoelectronic and microelectronic components with important applications span from energy harvesting to telecommunic
Externí odkaz:
https://doaj.org/article/75cc2344f32242249b755950fd805ff1
Publikováno v:
Frontiers in Materials, Vol 6 (2019)
The atomic force microscope (AFM) empowers research into nanoscale structural and functional material properties. Recently, the scope of application has broadened with the arrival of conductance tomography, a technique for mapping current in three-di
Externí odkaz:
https://doaj.org/article/5facffdc2b57446580d1b2e28249a3f0