EP3469521A4 - Neuronales netzwerk und verfahren zum trainieren eines neuronalen netzwerks - Google Patents

Neuronales netzwerk und verfahren zum trainieren eines neuronalen netzwerks Download PDF

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Publication number
EP3469521A4
EP3469521A4 EP17811082.1A EP17811082A EP3469521A4 EP 3469521 A4 EP3469521 A4 EP 3469521A4 EP 17811082 A EP17811082 A EP 17811082A EP 3469521 A4 EP3469521 A4 EP 3469521A4
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European Patent Office
Prior art keywords
neuronal network
training
neuronal
network
Prior art date
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Withdrawn
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EP17811082.1A
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English (en)
French (fr)
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EP3469521A1 (de
Inventor
Dmitri PESCIANSCHI
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Progress Inc
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Progress Inc
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Priority claimed from US15/178,137 external-priority patent/US9619749B2/en
Priority claimed from US15/449,614 external-priority patent/US10423694B2/en
Application filed by Progress Inc filed Critical Progress Inc
Publication of EP3469521A1 publication Critical patent/EP3469521A1/de
Publication of EP3469521A4 publication Critical patent/EP3469521A4/de
Withdrawn legal-status Critical Current

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    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0499Feedforward networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G06N3/065Analogue means
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/082Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/09Supervised learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks

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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)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Computational Linguistics (AREA)
  • Neurology (AREA)
  • Image Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
EP17811082.1A 2016-06-09 2017-06-09 Neuronales netzwerk und verfahren zum trainieren eines neuronalen netzwerks Withdrawn EP3469521A4 (de)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US15/178,137 US9619749B2 (en) 2014-03-06 2016-06-09 Neural network and method of neural network training
US15/449,614 US10423694B2 (en) 2014-03-06 2017-03-03 Neural network and method of neural network training
PCT/US2017/036758 WO2017214507A1 (en) 2016-06-09 2017-06-09 Neural network and method of neural network training

Publications (2)

Publication Number Publication Date
EP3469521A1 EP3469521A1 (de) 2019-04-17
EP3469521A4 true EP3469521A4 (de) 2020-02-26

Family

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Family Applications (1)

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EP17811082.1A Withdrawn EP3469521A4 (de) 2016-06-09 2017-06-09 Neuronales netzwerk und verfahren zum trainieren eines neuronalen netzwerks

Country Status (5)

Country Link
EP (1) EP3469521A4 (de)
JP (1) JP7041078B2 (de)
KR (1) KR102558300B1 (de)
CN (1) CN109416758A (de)
WO (1) WO2017214507A1 (de)

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US11454968B2 (en) * 2018-02-28 2022-09-27 Micron Technology, Inc. Artificial neural network integrity verification
US11640522B2 (en) 2018-12-13 2023-05-02 Tybalt, Llc Computational efficiency improvements for artificial neural networks
US11562231B2 (en) * 2018-09-03 2023-01-24 Tesla, Inc. Neural networks for embedded devices
CN109799439B (zh) * 2019-03-29 2021-04-13 云南电网有限责任公司电力科学研究院 一种绝缘多角度倾斜划伤电缆受潮实验评估方法及装置
CN110135557B (zh) * 2019-04-11 2023-06-02 上海集成电路研发中心有限公司 一种图像处理系统的神经网络拓扑架构
CN110111234B (zh) * 2019-04-11 2023-12-15 上海集成电路研发中心有限公司 一种基于神经网络的图像处理系统架构
CN110046513B (zh) * 2019-04-11 2023-01-03 长安大学 基于Hopfield混沌神经网络的明文关联图像加密方法
KR102675806B1 (ko) 2019-05-03 2024-06-18 삼성전자주식회사 영상 처리 장치 및 그 영상 처리 방법
US11361218B2 (en) * 2019-05-31 2022-06-14 International Business Machines Corporation Noise and signal management for RPU array
CN110533182B (zh) * 2019-08-01 2025-06-27 北京三快在线科技有限公司 一种数据处理方法及装置
US10726331B1 (en) * 2019-08-26 2020-07-28 International Business Machines Corporation Neural network circuits providing early integration before analog-to-digital conversion
WO2021073752A1 (en) * 2019-10-18 2021-04-22 Huawei Technologies Co., Ltd. Design and training of binary neurons and binary neural networks with error correcting codes
US11714999B2 (en) 2019-11-15 2023-08-01 International Business Machines Corporation Neuromorphic device with crossbar array structure storing both weights and neuronal states of neural networks
KR102410166B1 (ko) * 2019-11-27 2022-06-20 고려대학교 산학협력단 이종 곱셈-누셈 유닛을 이용하는 심층 신경망의 가속기
US20210303975A1 (en) * 2020-03-25 2021-09-30 Arm Limited Compression and decompression of weight values
CN111461308B (zh) * 2020-04-14 2023-06-30 中国人民解放军国防科技大学 忆阻神经网络及权值训练方法
JP7493398B2 (ja) 2020-07-03 2024-05-31 日本放送協会 変換装置、学習装置、およびプログラム
CN111815640B (zh) * 2020-07-21 2022-05-03 江苏经贸职业技术学院 一种基于忆阻器的rbf神经网络医学图像分割算法
CN112215344B (zh) * 2020-09-30 2025-03-21 清华大学 神经网络电路的校正方法以及设计方法
US12488250B2 (en) * 2020-11-02 2025-12-02 International Business Machines Corporation Weight repetition on RPU crossbar arrays
US12314844B2 (en) 2021-06-07 2025-05-27 International Business Machines Corporation Extraction of weight values in resistive processing unit array
CN113570048B (zh) * 2021-06-17 2022-05-31 南方科技大学 基于电路仿真的忆阻器阵列神经网络的构建及优化方法
KR102514652B1 (ko) * 2021-11-19 2023-03-29 서울대학교산학협력단 뉴로모픽 소자를 위한 가중치 전사 장치 및 이를 이용한 가중치 전사 방법
CN115358389B (zh) * 2022-09-01 2024-08-20 清华大学 神经网络的训练误差降低方法、装置、电子设备及介质
WO2024206841A1 (en) * 2023-03-31 2024-10-03 President And Fellows Of Harvard College Systems and methods for differentiable optical processors
CN121074527B (zh) * 2025-11-06 2026-03-03 浙江大学 一种基于谱范数正则的多层脉冲Hopfield网络图像分类方法

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US5600843A (en) * 1989-09-20 1997-02-04 Fujitsu Limited Ring systolic array system for synchronously performing matrix/neuron computation using data transferred through cyclic shift register connected in cascade of trays
US20160012330A1 (en) * 2014-03-06 2016-01-14 Progress, Inc. Neural network and method of neural network training

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US10055434B2 (en) * 2013-10-16 2018-08-21 University Of Tennessee Research Foundation Method and apparatus for providing random selection and long-term potentiation and depression in an artificial network

Patent Citations (2)

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US5600843A (en) * 1989-09-20 1997-02-04 Fujitsu Limited Ring systolic array system for synchronously performing matrix/neuron computation using data transferred through cyclic shift register connected in cascade of trays
US20160012330A1 (en) * 2014-03-06 2016-01-14 Progress, Inc. Neural network and method of neural network training

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
DMITRI PESCIANSCHI ET AL: "Analog and Digital Modeling of a Scalable Neural Network", PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (ICAI 2015), vol. II, 27 July 2015 (2015-07-27), XP055658955 *
DMITRI PESCIANSCHI ET AL: "Main Principles of the General Theory of Neural Network with Internal Feedback Neural Network", PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (ICAI 2015), vol. II, 27 July 2015 (2015-07-27), XP055658960 *
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YU-YI LIAO ET AL: "CMAC WITH CLUSTERING MEMORY AND ITS APPLICATION TO FACIAL EXPRESSION RECOGNITION", INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (IJPRAI), WORLD SCIENTIFIC PUBLISHING, SI, vol. 25, no. 7, 1 November 2011 (2011-11-01), pages 1055 - 1072, XP001570451, ISSN: 0218-0014, DOI: 10.1142/S0218001411008968 *

Also Published As

Publication number Publication date
EP3469521A1 (de) 2019-04-17
WO2017214507A1 (en) 2017-12-14
CN109416758A (zh) 2019-03-01
JP2019519045A (ja) 2019-07-04
KR20190016539A (ko) 2019-02-18
KR102558300B1 (ko) 2023-07-21
JP7041078B2 (ja) 2022-03-23

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