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Neuromorphic Silicon Photonics for Artificial Intelligence
Bicky A. Marquez
, Chaoran Huang
,
Paul R. Prucnal
, Bhavin J. Shastri
Electrical and Computer Engineering
Princeton Materials Institute
Research output
:
Chapter in Book/Report/Conference proceeding
›
Chapter
3
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Scopus citations
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Keyphrases
Artificial Intelligence
100%
Neuromorphic Photonics
100%
Silicon Photonics
100%
Neuromorphic
100%
Machine Learning
50%
On chip
50%
Low Energy
50%
Mach-Zehnder Interferometer
50%
Waveguide
50%
Ring Resonator
50%
Parallelization
50%
Speed of Light
50%
Reconfigurable Architectures
50%
Analog Signal Processing
50%
Multiple Signals
50%
Proposed Architecture
50%
Neural Network Architecture
50%
Neuromorphic Computing
50%
Photonic Platform
50%
Energy Applications
50%
Architecture-centric
50%
Neuromorphic Architecture
50%
Neural Network Applications
50%
Task Analysis
50%
Reservoir Computing
50%
Forward Propagation
50%
Efficiency Analysis
50%
Biological Time
50%
Busing
50%
On-chip Learning
50%
High Bandwidth
50%
Low Latency
50%
Bandwidth Limitation
50%
Computer Science
Silicon Photonics
100%
Artificial Intelligence
100%
Machine Learning
100%
Learning System
100%
Neural Network
50%
Parallelism
50%
reconfigurable architecture
50%
Neural Network Architecture
50%
Reservoir Computing
50%
Forward Propagation
50%
Zehnder Interferometer
50%
Single Waveguide
50%
ring resonator
50%
Material Science
Silicon
100%
Resonator
50%
Waveguide
50%
Interferometer
50%
Neuromorphic Computing
50%