Zobrazeno 1 - 10
of 374
pro vyhledávání: '"Bhaskaran, Harish"'
Autor:
Yang, Guoce, Wang, Mengyun, Lee, June Sang, Farmakidis, Nikolaos, Shields, Joe, de Galarreta, Carlota Ruiz, Kendall, Stuart, Bertolotti, Jacopo, Moskalenko, Andriy, Huang, Kairan, Alù, Andrea, Wright, C. David, Bhaskaran, Harish
The next generation of smart imaging and vision systems will require compact and tunable optical computing hardware to perform high-speed and low-power image processing. These requirements are driving the development of computing metasurfaces to real
Externí odkaz:
http://arxiv.org/abs/2409.10976
Autor:
Brückerhoff-Plückelmann, Frank, Borras, Hendrik, Klein, Bernhard, Varri, Akhil, Becker, Marlon, Dijkstra, Jelle, Brückerhoff, Martin, Wright, C. David, Salinga, Martin, Bhaskaran, Harish, Risse, Benjamin, Fröning, Holger, Pernice, Wolfram
Biological neural networks effortlessly tackle complex computational problems and excel at predicting outcomes from noisy, incomplete data, a task that poses significant challenges to traditional processors. Artificial neural networks (ANNs), inspire
Externí odkaz:
http://arxiv.org/abs/2401.17915
Autor:
Lugnan, Alessio, Aggarwal, Samarth, Brückerhoff-Plückelmann, Frank, Wright, C. David, Pernice, Wolfram H. P., Bhaskaran, Harish, Bienstman, Peter
Plastic self-adaptation, nonlinear recurrent dynamics and multi-scale memory are desired features in hardware implementations of neural networks, because they enable them to learn, adapt and process information similarly to the way biological brains
Externí odkaz:
http://arxiv.org/abs/2312.03802
Autor:
Lopez-Rodriguez, Bruno, Van Der Kolk, Roald, Aggarwal, Samarth, Sharma, Naresh, Li, Zizheng, Van Der Plaats, Daniel, Scholte, Thomas, Chang, Jin, Pereira, Silvania F., Groeblacher, Simon, Bhaskaran, Harish, Zadeh, Iman Esmaeil Zadeh
Integrated photonic platforms have proliferated in recent years, each demonstrating its own unique strengths and shortcomings. However, given the processing incompatibilities of different platforms, a formidable challenge in the field of integrated p
Externí odkaz:
http://arxiv.org/abs/2306.04491
Autor:
Zhou, Wen, Dong, Bowei, Farmakidis, Nikolaos, Li, Xuan, Youngblood, Nathan, Huang, Kairan, He, Yuhan, Wright, C. David, Pernice, Wolfram H. P., Bhaskaran, Harish
Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid photonic-electronic processing has not achieved computational success.
Externí odkaz:
http://arxiv.org/abs/2304.14302
Autor:
Aggarwal Samarth, Farmakidis Nikolaos, Dong Bowei, Lee June Sang, Wang Mengyun, Xu Zhiyun, Bhaskaran Harish
Publikováno v:
Nanophotonics, Vol 13, Iss 12, Pp 2223-2229 (2024)
In the past decade, the proliferation of modern telecommunication technologies, including 5G, and the widespread adoption of the Internet-of-things (IoT) have led to an unprecedented surge in data generation and transmission. This surge has created a
Externí odkaz:
https://doaj.org/article/adc7e9414ec44cf3a8ff484e78d4bb9d
Autor:
Lee June Sang, Farmakidis Nikolaos, Aggarwal Samarth, Dong Bowei, Zhou Wen, Pernice Wolfram H. P., Bhaskaran Harish
Publikováno v:
Nanophotonics, Vol 13, Iss 12, Pp 2117-2125 (2024)
Fast modulation of optical signals that carry multidimensional information in the form of wavelength, phase or polarization has fueled an explosion of interest in integrated photonics. This interest however masks a significant challenge which is that
Externí odkaz:
https://doaj.org/article/f8962950d4304b98a44221f8fdd4bdb8
Neural processing on devices and circuits is fast becoming a popular approach to emulate biological neural networks. Elaborate CMOS and memristive technologies have been employed to achieve this, including chalcogenide-based in-memory computing conce
Externí odkaz:
http://arxiv.org/abs/2107.00915
Autor:
Christensen, Dennis V., Dittmann, Regina, Linares-Barranco, Bernabé, Sebastian, Abu, Gallo, Manuel Le, Redaelli, Andrea, Slesazeck, Stefan, Mikolajick, Thomas, Spiga, Sabina, Menzel, Stephan, Valov, Ilia, Milano, Gianluca, Ricciardi, Carlo, Liang, Shi-Jun, Miao, Feng, Lanza, Mario, Quill, Tyler J., Keene, Scott T., Salleo, Alberto, Grollier, Julie, Marković, Danijela, Mizrahi, Alice, Yao, Peng, Yang, J. Joshua, Indiveri, Giacomo, Strachan, John Paul, Datta, Suman, Vianello, Elisa, Valentian, Alexandre, Feldmann, Johannes, Li, Xuan, Pernice, Wolfram H. P., Bhaskaran, Harish, Furber, Steve, Neftci, Emre, Scherr, Franz, Maass, Wolfgang, Ramaswamy, Srikanth, Tapson, Jonathan, Panda, Priyadarshini, Kim, Youngeun, Tanaka, Gouhei, Thorpe, Simon, Bartolozzi, Chiara, Cleland, Thomas A., Posch, Christoph, Liu, Shih-Chii, Panuccio, Gabriella, Mahmud, Mufti, Mazumder, Arnab Neelim, Hosseini, Morteza, Mohsenin, Tinoosh, Donati, Elisa, Tolu, Silvia, Galeazzi, Roberto, Christensen, Martin Ejsing, Holm, Sune, Ielmini, Daniele, Pryds, N.
Publikováno v:
Neuromorph. Comput. Eng. 2 022501 (2022)
Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This dat
Externí odkaz:
http://arxiv.org/abs/2105.05956