WO2020101863A3 - Hybrid opto-electronic neural networks and methods for utilization thereof - Google Patents

Hybrid opto-electronic neural networks and methods for utilization thereof Download PDF

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Publication number
WO2020101863A3
WO2020101863A3 PCT/US2019/058178 US2019058178W WO2020101863A3 WO 2020101863 A3 WO2020101863 A3 WO 2020101863A3 US 2019058178 W US2019058178 W US 2019058178W WO 2020101863 A3 WO2020101863 A3 WO 2020101863A3
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WO
WIPO (PCT)
Prior art keywords
utilization
optical
methods
neural networks
d2nn
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Application number
PCT/US2019/058178
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French (fr)
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WO2020101863A2 (en
Inventor
Yongxi Tan
Jin Yang
Yimeng Li
Xiang Liu
Ning Cheng
Huaxia WANG
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Futurewei Technologies, Inc.
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Publication date
Application filed by Futurewei Technologies, Inc. filed Critical Futurewei Technologies, Inc.
Priority to PCT/US2019/058178 priority Critical patent/WO2020101863A2/en
Publication of WO2020101863A2 publication Critical patent/WO2020101863A2/en
Publication of WO2020101863A3 publication Critical patent/WO2020101863A3/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/067—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using optical means
    • G06N3/0675—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using optical means using electro-optical, acousto-optical or opto-electronic means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/048—Activation functions

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Computational Linguistics (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Neurology (AREA)
  • Holo Graphy (AREA)
  • Optical Transform (AREA)
  • Optical Communication System (AREA)
  • Optical Modulation, Optical Deflection, Nonlinear Optics, Optical Demodulation, Optical Logic Elements (AREA)

Abstract

A hybrid neural network (NN) includes an optical diffractive NN (D2NN) comprising a diffractive network configured to implement neural computing in an optical domain, and a spatially incoherent light array operatively coupled to the optical D2NN, the spatially incoherent light array including an array of coherent light sources, and the spatially incoherent light array configured to illuminate the optical D2NN.
PCT/US2019/058178 2019-10-25 2019-10-25 Hybrid opto-electronic neural networks and methods for utilization thereof WO2020101863A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/US2019/058178 WO2020101863A2 (en) 2019-10-25 2019-10-25 Hybrid opto-electronic neural networks and methods for utilization thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/US2019/058178 WO2020101863A2 (en) 2019-10-25 2019-10-25 Hybrid opto-electronic neural networks and methods for utilization thereof

Publications (2)

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WO2020101863A2 WO2020101863A2 (en) 2020-05-22
WO2020101863A3 true WO2020101863A3 (en) 2020-08-27

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Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112101514B (en) * 2020-07-27 2022-06-07 北京航空航天大学 Diffraction neural network adopting pyramid structure diffraction layer for light supplement and implementation method
WO2022056422A1 (en) * 2020-09-14 2022-03-17 The Regents Of The University Of California Ensemble learning of diffractive neural networks
CN112700000A (en) * 2020-12-11 2021-04-23 北京信息科技大学 Photoelectric hybrid deep convolution neural network method
JP7395774B2 (en) * 2020-12-18 2023-12-11 株式会社フジクラ optical calculation system
CN115222034A (en) * 2022-07-27 2022-10-21 董毅博 Three-dimensional photonic chip architecture based on VCSEL array, application of three-dimensional photonic chip architecture and DNNs structure calculation method
CN116957031B (en) * 2023-07-24 2024-05-24 浙江大学 Photoelectric computer based on optical multi-neuron activation function module

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019200289A1 (en) * 2018-04-13 2019-10-17 The Regents Of The University Of California Devices and methods employing optical-based machine learning using diffractive deep neural networks

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019200289A1 (en) * 2018-04-13 2019-10-17 The Regents Of The University Of California Devices and methods employing optical-based machine learning using diffractive deep neural networks

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
JUTAMULIA S ET AL: "Overview of hybrid optical neural networks", OPTICS AND LASER TECHNOLOGY, ELSEVIER SCIENCE PUBLISHERS BV., AMSTERDAM, NL, vol. 28, no. 2, 1 March 1996 (1996-03-01), pages 59 - 72, XP004026142, ISSN: 0030-3992, DOI: 10.1016/0030-3992(95)00070-4 *
SHUMING JIAO ET AL: "Optical machine learning with incoherent light and a single-pixel detector", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 24 April 2019 (2019-04-24), XP081173176 *
XING LIN ET AL: "All-optical machine learning using diffractive deep neural networks", SCIENCE, vol. 361, no. 6406, 7 September 2018 (2018-09-07), US, pages 1004 - 1008, XP055711299, ISSN: 0036-8075, DOI: 10.1126/science.aat8084 *

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