Photonic neural networks based on integrated silicon microresonators
Recent progress in artificial intelligence (AI) has boosted the computational possibilities in
fields in which standard computers are not able to perform adequately. The AI paradigm is to …
fields in which standard computers are not able to perform adequately. The AI paradigm is to …
Time delay reservoir computing with a silicon microring resonator and a fiber-based optical feedback loop
Silicon microring resonators serve as critical components in integrated photonic neural
network implementations, owing to their compact footprint, compatibility with CMOS …
network implementations, owing to their compact footprint, compatibility with CMOS …
Programmable Photonic Extreme Learning Machines
JR Rausell-Campo, A Hurtado, D Pérez-López… - arXiv preprint arXiv …, 2024 - arxiv.org
Photonic neural networks offer a promising alternative to traditional electronic systems for
machine learning accelerators due to their low latency and energy efficiency. However, the …
machine learning accelerators due to their low latency and energy efficiency. However, the …
Photonic Extreme Learning Machines Using Hexagonal Programmable Waveguide Meshes
JRR Campo, DP López… - 2024 IEEE Silicon …, 2024 - ieeexplore.ieee.org
We propose employing a hexagonal mesh as a Programmable Photonic Extreme Learning
Machine. Input encoding, random matrix multiplication and nonlinearity are performed on …
Machine. Input encoding, random matrix multiplication and nonlinearity are performed on …
Experimental Demonstration of a Photonic Extreme Learning Machine with an Array of Microresonators
The training process of a feed-forward neural network is typically power-and time-
consuming because it requires optimization of the output response through a gradient …
consuming because it requires optimization of the output response through a gradient …