Conference proceeding
Optoelectronic Quantum Capacitors for Configurable Neural Photonic Networks
2019 Conference on Lasers and Electro-Optics (CLEO), v 2019, pp 1-2
May 2019
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
An optically-controlled quantum capacitor is described as a memristive behaving neuron in a crossbar neural network. Specifically, activation value, weight, and bias for each neuron are dynamically controlled with light intensity, applied gate voltage, and a sampling frequency, respectively; therefore, it provides a programmable capacitive neural network with dynamic configurability.
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Details
- Title
- Optoelectronic Quantum Capacitors for Configurable Neural Photonic Networks
- Creators
- Pouya Dianat - Drexel UniversityAnna Persano - National Research Council (IMM-CNR), Institute for Microelectronics and Microsystems-Unit of Lecce, Lecce, 73100, ItalyFabio Quaranta - National Research Council (IMM-CNR), Institute for Microelectronics and Microsystems-Unit of Lecce, Lecce, 73100, ItalyAdriano Cola - National Research Council (IMM-CNR), Institute for Microelectronics and Microsystems-Unit of Lecce, Lecce, 73100, ItalyBahram Nabet - Drexel UniversityIEEE
- Publication Details
- 2019 Conference on Lasers and Electro-Optics (CLEO), v 2019, pp 1-2
- Conference
- 2019 Conference on Lasers and Electro-Optics (CLEO)
- Publisher
- OSA
- Number of pages
- 1
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000482226303108
- Scopus ID
- 2-s2.0-85068103188
- Other Identifier
- 991019170357004721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Electrical & Electronic
- Optics
- Physics, Applied