TWI822792B - 將人工神經網路中之活動特徵化之方法及包含一或多個可執行該方法之計算機之系統 - Google Patents

將人工神經網路中之活動特徵化之方法及包含一或多個可執行該方法之計算機之系統 Download PDF

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TWI822792B
TWI822792B TW108119813A TW108119813A TWI822792B TW I822792 B TWI822792 B TW I822792B TW 108119813 A TW108119813 A TW 108119813A TW 108119813 A TW108119813 A TW 108119813A TW I822792 B TWI822792 B TW I822792B
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neural network
activity
artificial neural
patterns
input
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TW108119813A
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TW202001693A (zh
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亨利 馬克拉姆
藍 利维
凱瑟琳 潘蜜拉 波樂華樂德
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瑞士商Inait公司
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Priority claimed from US16/004,757 external-priority patent/US11893471B2/en
Priority claimed from US16/004,796 external-priority patent/US20190378000A1/en
Priority claimed from US16/004,837 external-priority patent/US11663478B2/en
Priority claimed from US16/004,671 external-priority patent/US11972343B2/en
Priority claimed from US16/004,635 external-priority patent/US20190378007A1/en
Application filed by 瑞士商Inait公司 filed Critical 瑞士商Inait公司
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR 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; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/049Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/004Artificial life, i.e. computing arrangements simulating life
    • G06N3/006Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/004Artificial life, i.e. computing arrangements simulating life
    • G06N3/008Artificial life, i.e. computing arrangements simulating life based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. based on robots replicating pets or humans in their appearance or behaviour
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/044Recurrent networks, e.g. Hopfield networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/01Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
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  • Artificial Intelligence (AREA)
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  • Molecular Biology (AREA)
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  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
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TW108119813A 2018-06-11 2019-06-06 將人工神經網路中之活動特徵化之方法及包含一或多個可執行該方法之計算機之系統 TWI822792B (zh)

Applications Claiming Priority (10)

Application Number Priority Date Filing Date Title
US16/004,757 US11893471B2 (en) 2018-06-11 2018-06-11 Encoding and decoding information and artificial neural networks
US16/004,671 2018-06-11
US16/004,796 US20190378000A1 (en) 2018-06-11 2018-06-11 Characterizing activity in a recurrent artificial neural network
US16/004,796 2018-06-11
US16/004,837 US11663478B2 (en) 2018-06-11 2018-06-11 Characterizing activity in a recurrent artificial neural network
US16/004,671 US11972343B2 (en) 2018-06-11 2018-06-11 Encoding and decoding information
US16/004,757 2018-06-11
US16/004,635 US20190378007A1 (en) 2018-06-11 2018-06-11 Characterizing activity in a recurrent artificial neural network
US16/004,635 2018-06-11
US16/004,837 2018-06-11

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TW202001693A TW202001693A (zh) 2020-01-01
TWI822792B true TWI822792B (zh) 2023-11-21

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EP (5) EP3803699A1 (fr)
KR (5) KR102497238B1 (fr)
CN (5) CN112567387A (fr)
TW (1) TWI822792B (fr)
WO (5) WO2019238483A1 (fr)

Families Citing this family (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11615285B2 (en) 2017-01-06 2023-03-28 Ecole Polytechnique Federale De Lausanne (Epfl) Generating and identifying functional subnetworks within structural networks
US11893471B2 (en) 2018-06-11 2024-02-06 Inait Sa Encoding and decoding information and artificial neural networks
US11663478B2 (en) 2018-06-11 2023-05-30 Inait Sa Characterizing activity in a recurrent artificial neural network
US11972343B2 (en) 2018-06-11 2024-04-30 Inait Sa Encoding and decoding information
US11569978B2 (en) 2019-03-18 2023-01-31 Inait Sa Encrypting and decrypting information
US11652603B2 (en) 2019-03-18 2023-05-16 Inait Sa Homomorphic encryption
US11610134B2 (en) * 2019-07-08 2023-03-21 Vianai Systems, Inc. Techniques for defining and executing program code specifying neural network architectures
US11580401B2 (en) 2019-12-11 2023-02-14 Inait Sa Distance metrics and clustering in recurrent neural networks
US11816553B2 (en) 2019-12-11 2023-11-14 Inait Sa Output from a recurrent neural network
US11651210B2 (en) 2019-12-11 2023-05-16 Inait Sa Interpreting and improving the processing results of recurrent neural networks
US11797827B2 (en) 2019-12-11 2023-10-24 Inait Sa Input into a neural network
TWI769466B (zh) * 2020-06-17 2022-07-01 台達電子工業股份有限公司 類神經網路系統及其操作方法
CN112073217B (zh) * 2020-08-07 2023-03-24 之江实验室 一种多网络结构差异向量化方法及装置
CN113219358A (zh) * 2021-04-29 2021-08-06 东软睿驰汽车技术(沈阳)有限公司 电池包健康状态计算方法、系统及电子设备
TWI769875B (zh) * 2021-06-24 2022-07-01 國立中央大學 深度學習網路裝置、其使用的記憶體存取方法與非揮發性儲存媒介
CN113626721B (zh) * 2021-10-12 2022-01-25 中国科学院自动化研究所 基于遗憾探索的推荐方法、装置、电子设备与存储介质

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7958071B2 (en) * 2007-04-19 2011-06-07 Hewlett-Packard Development Company, L.P. Computational nodes and computational-node networks that include dynamical-nanodevice connections
JP5844286B2 (ja) * 2010-02-05 2016-01-13 エコール・ポリテクニーク・フェデラル・ドゥ・ローザンヌ (ウ・ペ・エフ・エル)Ecole Polytechnique Federalede Lausanne (Epfl) ニューラルネットワークの組織化
US8170971B1 (en) * 2011-09-28 2012-05-01 Ava, Inc. Systems and methods for providing recommendations based on collaborative and/or content-based nodal interrelationships
US20180053114A1 (en) * 2014-10-23 2018-02-22 Brighterion, Inc. Artificial intelligence for context classifier
CN106156845A (zh) * 2015-03-23 2016-11-23 日本电气株式会社 一种用于构建神经网络的方法和设备
CN105095966B (zh) * 2015-07-16 2018-08-21 北京灵汐科技有限公司 人工神经网络和脉冲神经网络的混合计算系统
US20180005111A1 (en) * 2016-06-30 2018-01-04 International Business Machines Corporation Generalized Sigmoids and Activation Function Learning
US11544539B2 (en) * 2016-09-29 2023-01-03 Tsinghua University Hardware neural network conversion method, computing device, compiling method and neural network software and hardware collaboration system
US10748060B2 (en) * 2016-10-14 2020-08-18 Intel Corporation Pre-synaptic learning using delayed causal updates
CN107247989B (zh) * 2017-06-15 2020-11-24 北京图森智途科技有限公司 一种实时的计算机视觉处理方法及装置
CN107423814A (zh) * 2017-07-31 2017-12-01 南昌航空大学 一种采用深度卷积神经网络建立动态网络模型的方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
期刊 MICHAEL W. REIMANN ET AL,Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function,FRONTIERS IN COMPUTATIONAL NEUROSIENCE vol. 11,12 June 2017

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Publication number Publication date
EP3803707A1 (fr) 2021-04-14
EP3803705A1 (fr) 2021-04-14
CN112567390A (zh) 2021-03-26
CN112567388A (zh) 2021-03-26
KR20210008418A (ko) 2021-01-21
KR20210008417A (ko) 2021-01-21
CN112567389A (zh) 2021-03-26
KR20210008858A (ko) 2021-01-25
KR102497238B1 (ko) 2023-02-07
KR20210008419A (ko) 2021-01-21
EP3803699A1 (fr) 2021-04-14
KR102526132B1 (ko) 2023-04-26
CN112567387A (zh) 2021-03-26
KR102488042B1 (ko) 2023-01-12
KR20210010894A (ko) 2021-01-28
WO2019238483A1 (fr) 2019-12-19
KR102465409B1 (ko) 2022-11-09
WO2019238523A1 (fr) 2019-12-19
TW202001693A (zh) 2020-01-01
EP3803706A1 (fr) 2021-04-14
CN112585621A (zh) 2021-03-30
WO2019238522A1 (fr) 2019-12-19
WO2019238512A1 (fr) 2019-12-19
EP3803708A1 (fr) 2021-04-14
KR102475411B1 (ko) 2022-12-07
WO2019238513A1 (fr) 2019-12-19

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