Spatio-Temporal Photonic Liquid State and Extreme Learning Machines

Abstract

The proposed research aims at designing neurmorphic photonic computers, known as a liquid-state machine (LSM) and extreme-learning machines (ELM). We will exploit complex high-speed spatio-temporal dynamics generated by a large-scale interconnected photonics architecture on complex classification problems with application in the context of big data.

Document Details

Document Type
DoD Grant Award
Publication Date
May 02, 2017
Source ID
FA95501710072

Entities

People

  • Damien Rontani

Organizations

  • Air Force Office of Scientific Research
  • CentraleSupélec
  • United States Air Force

Tags

Readers

  • Neural Network Machine Learning.
  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.