BR112016006482A2 - métodos e aparelho para implementação de indicadores de grupo para modelos neurais - Google Patents

métodos e aparelho para implementação de indicadores de grupo para modelos neurais

Info

Publication number
BR112016006482A2
BR112016006482A2 BR112016006482A BR112016006482A BR112016006482A2 BR 112016006482 A2 BR112016006482 A2 BR 112016006482A2 BR 112016006482 A BR112016006482 A BR 112016006482A BR 112016006482 A BR112016006482 A BR 112016006482A BR 112016006482 A2 BR112016006482 A2 BR 112016006482A2
Authority
BR
Brazil
Prior art keywords
group
methods
group indicators
indicators
neural models
Prior art date
Application number
BR112016006482A
Other languages
English (en)
Portuguese (pt)
Inventor
Jonathan Julian David
Alexander Levin Jeffrey
Baginsky Gehlhaar Jeffrey
Original Assignee
Qualcomm Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Qualcomm Inc filed Critical Qualcomm Inc
Publication of BR112016006482A2 publication Critical patent/BR112016006482A2/pt

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/049—Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
    • G06N3/0499—Feedforward networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Molecular Biology (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Image Analysis (AREA)
  • Nitrogen Condensed Heterocyclic Rings (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Feedback Control In General (AREA)
BR112016006482A 2013-09-25 2014-08-18 métodos e aparelho para implementação de indicadores de grupo para modelos neurais BR112016006482A2 (pt)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201361882465P 2013-09-25 2013-09-25
US14/268,152 US9959499B2 (en) 2013-09-25 2014-05-02 Methods and apparatus for implementation of group tags for neural models
PCT/US2014/051469 WO2015047589A2 (en) 2013-09-25 2014-08-18 Methods and apparatus for implementation of group tags for neural models

Publications (1)

Publication Number Publication Date
BR112016006482A2 true BR112016006482A2 (pt) 2017-08-01

Family

ID=52691891

Family Applications (1)

Application Number Title Priority Date Filing Date
BR112016006482A BR112016006482A2 (pt) 2013-09-25 2014-08-18 métodos e aparelho para implementação de indicadores de grupo para modelos neurais

Country Status (9)

Country Link
US (1) US9959499B2 (enExample)
EP (1) EP3050004A2 (enExample)
JP (1) JP2016536657A (enExample)
KR (1) KR20160058825A (enExample)
CN (1) CN105556543B (enExample)
BR (1) BR112016006482A2 (enExample)
CA (1) CA2921831A1 (enExample)
TW (1) TW201523463A (enExample)
WO (1) WO2015047589A2 (enExample)

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WO2017068490A1 (en) * 2015-10-23 2017-04-27 Semiconductor Energy Laboratory Co., Ltd. Semiconductor device and electronic device
CN108255775A (zh) * 2016-12-28 2018-07-06 上海磁宇信息科技有限公司 用于细胞阵列计算系统的细胞阵列总线广播方法
US20190102669A1 (en) * 2017-09-29 2019-04-04 Intel Corporation Global and local time-step determination schemes for neural networks
US11195079B2 (en) * 2017-11-22 2021-12-07 Intel Corporation Reconfigurable neuro-synaptic cores for spiking neural network
CN108830379B (zh) * 2018-05-23 2021-12-17 电子科技大学 一种基于参数量化共享的神经形态处理器
KR102756358B1 (ko) 2018-12-18 2025-01-17 삼성전자주식회사 검출기, 객체 검출 방법, 학습기 및 도메인 변환을 위한 학습 방법
US11625583B2 (en) * 2019-02-13 2023-04-11 Mipsology SAS Quality monitoring and hidden quantization in artificial neural network computations
EP4035127A4 (en) 2019-09-24 2023-10-18 Applied Materials, Inc. INTERACTIVE TRAINING OF A MACHINE LEARNING MODEL FOR TISSUE SEGMENTATION
CN113065647B (zh) * 2021-03-30 2023-04-25 西安电子科技大学 加速神经网络的计算-存储通信系统及通信方法
CN115169547B (zh) * 2022-09-09 2022-11-29 深圳时识科技有限公司 神经形态芯片及电子设备

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Publication number Priority date Publication date Assignee Title
US5276769A (en) * 1989-03-13 1994-01-04 Sharp Kabushiki Kaisha Neural network learning apparatus and method
JP3172163B2 (ja) * 1990-05-07 2001-06-04 富士通株式会社 ニューラルネットワークにおける結合のグループ単位学習調整方式
JPH06348675A (ja) * 1993-06-07 1994-12-22 Ebara Corp ニューロコンピュータ応用機器およびこれを含む機械装置
AU7324396A (en) * 1996-11-05 1998-05-29 Millennium Interactive Limited Process control
JP2002251601A (ja) * 2001-02-22 2002-09-06 Fuji Xerox Co Ltd ニューラルネットワーク処理装置
US8630966B2 (en) 2009-01-27 2014-01-14 Salk Institute For Biological Studies Temporally dynamic artificial neural networks
US8504499B2 (en) 2009-07-15 2013-08-06 The Intellisis Corporation Constant memory implementation of a phase-model neural network
US20110055131A1 (en) * 2009-08-28 2011-03-03 Hung-Han Chen Method of universal computing device
US9129220B2 (en) 2010-07-07 2015-09-08 Qualcomm Incorporated Methods and systems for digital neural processing with discrete-level synapes and probabilistic STDP
US8738554B2 (en) 2011-09-16 2014-05-27 International Business Machines Corporation Event-driven universal neural network circuit
US8943008B2 (en) * 2011-09-21 2015-01-27 Brain Corporation Apparatus and methods for reinforcement learning in artificial neural networks
US8712939B2 (en) 2011-09-21 2014-04-29 Brain Corporation Tag-based apparatus and methods for neural networks
US9098811B2 (en) * 2012-06-04 2015-08-04 Brain Corporation Spiking neuron network apparatus and methods
US9129221B2 (en) 2012-05-07 2015-09-08 Brain Corporation Spiking neural network feedback apparatus and methods
US9256823B2 (en) * 2012-07-27 2016-02-09 Qualcomm Technologies Inc. Apparatus and methods for efficient updates in spiking neuron network

Also Published As

Publication number Publication date
CA2921831A1 (en) 2015-04-02
US9959499B2 (en) 2018-05-01
US20150088796A1 (en) 2015-03-26
CN105556543A (zh) 2016-05-04
KR20160058825A (ko) 2016-05-25
EP3050004A2 (en) 2016-08-03
WO2015047589A3 (en) 2015-05-21
CN105556543B (zh) 2018-11-23
JP2016536657A (ja) 2016-11-24
TW201523463A (zh) 2015-06-16
WO2015047589A2 (en) 2015-04-02

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Legal Events

Date Code Title Description
B06F Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]
B06U Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]
B11B Dismissal acc. art. 36, par 1 of ipl - no reply within 90 days to fullfil the necessary requirements