BR112016007313A2 - método automatizado para modificar dinâmica neural - Google Patents
método automatizado para modificar dinâmica neuralInfo
- Publication number
- BR112016007313A2 BR112016007313A2 BR112016007313A BR112016007313A BR112016007313A2 BR 112016007313 A2 BR112016007313 A2 BR 112016007313A2 BR 112016007313 A BR112016007313 A BR 112016007313A BR 112016007313 A BR112016007313 A BR 112016007313A BR 112016007313 A2 BR112016007313 A2 BR 112016007313A2
- Authority
- BR
- Brazil
- Prior art keywords
- dynamics
- automated method
- neurons
- neural dynamics
- modify neural
- Prior art date
Links
Classifications
-
- 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
- G06N3/049—Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- 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
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using 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
-
- 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
- G06N3/08—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)
- Software Systems (AREA)
- Computing Systems (AREA)
- Artificial Intelligence (AREA)
- Mathematical Physics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- General Health & Medical Sciences (AREA)
- Computational Linguistics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Neurology (AREA)
- Image Analysis (AREA)
- Separation Using Semi-Permeable Membranes (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
1/1 resumo método automatizado para modificar dinâmica neural um método para aperfeiçoar dinâmica neural inclui obter dinâmica de neurônios prototípicos. o método inclui também modificar parâmetros de um modelo de neurônio de modo que o modelo de neurônio corresponda à dinâmica de neurônios prototípicos. a dinâmica de neurônios compreende tensões de membrana e/ou temporização de picos.
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201361885950P | 2013-10-02 | 2013-10-02 | |
US14/066,599 US9305256B2 (en) | 2013-10-02 | 2013-10-29 | Automated method for modifying neural dynamics |
PCT/US2014/052131 WO2015050641A2 (en) | 2013-10-02 | 2014-08-21 | Automated method for modifying neural dynamics |
Publications (1)
Publication Number | Publication Date |
---|---|
BR112016007313A2 true BR112016007313A2 (pt) | 2017-08-01 |
Family
ID=52741128
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
BR112016007313A BR112016007313A2 (pt) | 2013-10-02 | 2014-08-21 | método automatizado para modificar dinâmica neural |
Country Status (8)
Country | Link |
---|---|
US (1) | US9305256B2 (pt) |
EP (1) | EP3053105A2 (pt) |
JP (1) | JP6092477B2 (pt) |
KR (1) | KR101700145B1 (pt) |
CN (1) | CN105637539B (pt) |
BR (1) | BR112016007313A2 (pt) |
CA (1) | CA2924048A1 (pt) |
WO (1) | WO2015050641A2 (pt) |
Families Citing this family (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10068170B2 (en) * | 2013-09-23 | 2018-09-04 | Oracle International Corporation | Minimizing global error in an artificial neural network |
JP2017102904A (ja) * | 2015-10-23 | 2017-06-08 | 株式会社半導体エネルギー研究所 | 半導体装置および電子機器 |
WO2018206405A1 (en) * | 2017-05-08 | 2018-11-15 | British Telecommunications Public Limited Company | Interoperation of machine learning algorithms |
US11216723B2 (en) * | 2017-08-11 | 2022-01-04 | Syntiant | Pulse-width modulated multiplier |
US11308382B2 (en) | 2017-08-25 | 2022-04-19 | International Business Machines Corporation | Neuromorphic synapses |
US10211856B1 (en) * | 2017-10-12 | 2019-02-19 | The Boeing Company | Hardware scalable channelizer utilizing a neuromorphic approach |
KR102251765B1 (ko) * | 2018-12-19 | 2021-05-14 | 한양대학교 산학협력단 | 뉴런 및 이를 포함하는 뉴로모픽 시스템 |
KR102249655B1 (ko) * | 2018-12-19 | 2021-05-10 | 한양대학교 산학협력단 | 뉴런 및 이를 포함하는 뉴로모픽 시스템 |
WO2021066504A1 (ko) * | 2019-10-02 | 2021-04-08 | 한국전자통신연구원 | 심층 신경망 구조 학습 및 경량화 방법 |
US20220301688A1 (en) * | 2019-10-09 | 2022-09-22 | University Of Southrn California | Geometric paradigm for nonlinear modeling and control of neural dynamics |
KR102453336B1 (ko) * | 2019-11-12 | 2022-10-12 | 한국전자기술연구원 | 스파이킹 뉴럴 네트워크를 위한 하이퍼 파라미터 최적화 방법과 장치 및 이를 이용한 연산 장치 |
CN111814973B (zh) * | 2020-07-18 | 2022-06-21 | 福州大学 | 一种适用于神经常微分方程网络计算的存内计算系统 |
CN115939883A (zh) | 2021-10-05 | 2023-04-07 | 泰科电子连接印度私有有限公司 | 用于增加拉出阻力的电缆保护盖 |
Family Cites Families (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
FR2881857B1 (fr) * | 2005-02-04 | 2008-05-23 | Bernard Angeniol | Outil informatique de prevision |
CN101441728B (zh) * | 2007-11-21 | 2010-09-08 | 新乡市起重机厂有限公司 | 门式起重机优化设计的神经网络方法 |
JP5155843B2 (ja) * | 2008-12-22 | 2013-03-06 | シャープ株式会社 | 情報処理装置及びこれを用いたニューラルネットワーク回路 |
US8250010B2 (en) * | 2009-05-21 | 2012-08-21 | International Business Machines Corporation | Electronic learning synapse with spike-timing dependent plasticity using unipolar memory-switching elements |
US8346712B2 (en) | 2009-11-24 | 2013-01-01 | King Fahd University Of Petroleum And Minerals | Method for identifying hammerstein models |
US20120023051A1 (en) | 2010-07-22 | 2012-01-26 | Ramin Pishehvar | Signal coding with adaptive neural network |
US8473439B2 (en) * | 2010-12-08 | 2013-06-25 | International Business Machines Corporation | Integrate and fire electronic neurons |
US8706250B2 (en) | 2010-12-23 | 2014-04-22 | Boston Scientific Neuromodulation Corporation | Neurostimulation system for implementing model-based estimate of neurostimulation effects |
US9092735B2 (en) | 2011-09-21 | 2015-07-28 | Qualcomm Incorporated | Method and apparatus for structural delay plasticity in spiking neural networks |
US9111222B2 (en) * | 2011-11-09 | 2015-08-18 | Qualcomm Incorporated | Method and apparatus for switching the binary state of a location in memory in a probabilistic manner to store synaptic weights of a neural network |
US20130204814A1 (en) * | 2012-02-08 | 2013-08-08 | Qualcomm Incorporated | Methods and apparatus for spiking neural computation |
-
2013
- 2013-10-29 US US14/066,599 patent/US9305256B2/en active Active
-
2014
- 2014-08-21 CA CA2924048A patent/CA2924048A1/en not_active Abandoned
- 2014-08-21 CN CN201480054405.1A patent/CN105637539B/zh active Active
- 2014-08-21 EP EP14761928.2A patent/EP3053105A2/en not_active Withdrawn
- 2014-08-21 WO PCT/US2014/052131 patent/WO2015050641A2/en active Application Filing
- 2014-08-21 JP JP2016519393A patent/JP6092477B2/ja active Active
- 2014-08-21 BR BR112016007313A patent/BR112016007313A2/pt not_active Application Discontinuation
- 2014-08-21 KR KR1020167010147A patent/KR101700145B1/ko active IP Right Grant
Also Published As
Publication number | Publication date |
---|---|
WO2015050641A2 (en) | 2015-04-09 |
US20150095273A1 (en) | 2015-04-02 |
EP3053105A2 (en) | 2016-08-10 |
US9305256B2 (en) | 2016-04-05 |
JP2016536664A (ja) | 2016-11-24 |
KR101700145B1 (ko) | 2017-01-26 |
JP6092477B2 (ja) | 2017-03-08 |
CN105637539A (zh) | 2016-06-01 |
CN105637539B (zh) | 2018-03-27 |
CA2924048A1 (en) | 2015-04-09 |
KR20160062052A (ko) | 2016-06-01 |
WO2015050641A3 (en) | 2015-06-04 |
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Legal Events
Date | Code | Title | Description |
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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 |