JP6571692B2 - メムリスティブニューラルネットワーク及びその形成方法 - Google Patents

メムリスティブニューラルネットワーク及びその形成方法 Download PDF

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JP6571692B2
JP6571692B2 JP2016573557A JP2016573557A JP6571692B2 JP 6571692 B2 JP6571692 B2 JP 6571692B2 JP 2016573557 A JP2016573557 A JP 2016573557A JP 2016573557 A JP2016573557 A JP 2016573557A JP 6571692 B2 JP6571692 B2 JP 6571692B2
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ファン クラウディオ ニノ、
ファン クラウディオ ニノ、
ジャック ディー． ケンダル、
ジャック ディー． ケンダル、
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ユニバーシティ オブ フロリダ リサーチ ファンデーション インコーポレーティッド
ユニバーシティ オブ フロリダ リサーチ ファンデーション インコーポレーティッド
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    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11C—STATIC STORES
    • G11C13/00—Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00, or G11C25/00
    • G11C13/0002—Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00, or G11C25/00 using resistive RAM [RRAM] elements
    • G11C13/0007—Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00, or G11C25/00 using resistive RAM [RRAM] elements comprising metal oxide memory material, e.g. perovskites
    • 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
    • G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G06N3/065—Analogue means
    • 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
    • G06N3/044—Recurrent networks, e.g. Hopfield 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
    • G06N3/049—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
    • G06N3/0495—Quantised networks; Sparse networks; Compressed 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
    • 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

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  • Metal-Oxide And Bipolar Metal-Oxide Semiconductor Integrated Circuits (AREA)
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JP2016573557A 2014-06-19 2015-06-05 メムリスティブニューラルネットワーク及びその形成方法 Active JP6571692B2 (ja)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201462014201P 2014-06-19 2014-06-19
US62/014,201 2014-06-19
PCT/US2015/034414 WO2015195365A1 (fr) 2014-06-19 2015-06-05 Réseaux neuronaux à nanofibres memristives

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JP2017527000A JP2017527000A (ja) 2017-09-14
JP6571692B2 true JP6571692B2 (ja) 2019-09-04

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EP (1) EP3158509A4 (fr)
JP (1) JP6571692B2 (fr)
KR (1) KR20170019414A (fr)
AU (1) AU2015277645B2 (fr)
BR (1) BR112016029682A2 (fr)
WO (1) WO2015195365A1 (fr)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10198691B2 (en) 2014-06-19 2019-02-05 University Of Florida Research Foundation, Inc. Memristive nanofiber neural networks
CN107533668B (zh) 2016-03-11 2021-01-26 慧与发展有限责任合伙企业 用于计算神经网络的节点值的硬件加速器和方法
EP3631800A4 (fr) * 2017-05-22 2021-04-07 University of Florida Research Foundation Apprentissage en profondeur dans des réseaux memristifs bipartites
WO2019195660A1 (fr) 2018-04-05 2019-10-10 Rain Neuromorphics Inc. Systèmes et procédés pour une multiplication efficace de matrice
US11450712B2 (en) 2020-02-18 2022-09-20 Rain Neuromorphics Inc. Memristive device
CN120046673B (zh) * 2025-04-23 2025-09-12 武汉工程大学 一种具有部分强化的操作性条件反射的忆阻神经网络电路

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KR0185757B1 (ko) * 1994-02-14 1999-05-15 정호선 혼돈 순환 신경회로망의 학습방법
JPH09185596A (ja) * 1996-01-08 1997-07-15 Ricoh Co Ltd パルス密度型信号処理回路網における結合係数更新方法
US7392230B2 (en) * 2002-03-12 2008-06-24 Knowmtech, Llc Physical neural network liquid state machine utilizing nanotechnology
US7359888B2 (en) * 2003-01-31 2008-04-15 Hewlett-Packard Development Company, L.P. Molecular-junction-nanowire-crossbar-based neural network
WO2008042900A2 (fr) * 2006-10-02 2008-04-10 University Of Florida Research Foundation, Inc. Extraction de caractéristique à base d'impulsions pour des enregistrements neuronaux
EP2230633A1 (fr) * 2009-03-17 2010-09-22 Commissariat à l'Énergie Atomique et aux Énergies Alternatives Circuit de réseau neuronal comprenant des synapses d'échelle nanométrique et des neurones CMOS
US8050078B2 (en) * 2009-10-27 2011-11-01 Hewlett-Packard Development Company, L.P. Nanowire-based memristor devices
US8433665B2 (en) * 2010-07-07 2013-04-30 Qualcomm Incorporated Methods and systems for three-memristor synapse with STDP and dopamine signaling
KR20140071813A (ko) * 2012-12-04 2014-06-12 삼성전자주식회사 파이버 상에 형성된 저항성 메모리 소자 및 그 제종 방법
US9418331B2 (en) * 2013-10-28 2016-08-16 Qualcomm Incorporated Methods and apparatus for tagging classes using supervised learning

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Publication number Publication date
JP2017527000A (ja) 2017-09-14
EP3158509A1 (fr) 2017-04-26
AU2015277645B2 (en) 2021-01-28
BR112016029682A2 (pt) 2018-07-10
KR20170019414A (ko) 2017-02-21
AU2015277645A1 (en) 2016-12-22
WO2015195365A1 (fr) 2015-12-23
EP3158509A4 (fr) 2018-02-28

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