CN105518721B - 用于在人工神经系统中实现断点确定单元的方法和装置 - Google Patents

用于在人工神经系统中实现断点确定单元的方法和装置 Download PDF

Info

Publication number
CN105518721B
CN105518721B CN201480048670.9A CN201480048670A CN105518721B CN 105518721 B CN105518721 B CN 105518721B CN 201480048670 A CN201480048670 A CN 201480048670A CN 105518721 B CN105518721 B CN 105518721B
Authority
CN
China
Prior art keywords
neuron
breakpoint
nervous system
condition
spike
Prior art date
Legal status (The legal status 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 status listed.)
Active
Application number
CN201480048670.9A
Other languages
English (en)
Chinese (zh)
Other versions
CN105518721A (zh
Inventor
M-D·N·卡洛伊
W·R·贝尔二世
R·金特达
V·兰甘
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Qualcomm Inc
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 CN105518721A publication Critical patent/CN105518721A/zh
Application granted granted Critical
Publication of CN105518721B publication Critical patent/CN105518721B/zh
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

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
    • G06N3/10—Interfaces, programming languages or software development kits, e.g. for simulating neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/36—Prevention of errors by analysis, debugging or testing of software
    • G06F11/362—Debugging of software
    • G06F11/3636—Debugging of software by tracing the execution of the program
    • 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
    • G06N3/0499—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
    • 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
    • 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
    • G06N3/088—Non-supervised learning, e.g. competitive learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Evolutionary Computation (AREA)
  • Molecular Biology (AREA)
  • Data Mining & Analysis (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Computer Hardware Design (AREA)
  • Quality & Reliability (AREA)
  • Image Analysis (AREA)
  • Debugging And Monitoring (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Neurology (AREA)
CN201480048670.9A 2013-09-03 2014-08-14 用于在人工神经系统中实现断点确定单元的方法和装置 Active CN105518721B (zh)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US201361873044P 2013-09-03 2013-09-03
US61/873,044 2013-09-03
US14/281,118 US9710749B2 (en) 2013-09-03 2014-05-19 Methods and apparatus for implementing a breakpoint determination unit in an artificial nervous system
US14/281,118 2014-05-19
PCT/US2014/051044 WO2015034640A2 (en) 2013-09-03 2014-08-14 Methods and apparatus for implementing a breakpoint determination unit in an artificial nervous system

Publications (2)

Publication Number Publication Date
CN105518721A CN105518721A (zh) 2016-04-20
CN105518721B true CN105518721B (zh) 2018-10-02

Family

ID=52584658

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201480048670.9A Active CN105518721B (zh) 2013-09-03 2014-08-14 用于在人工神经系统中实现断点确定单元的方法和装置

Country Status (7)

Country Link
US (1) US9710749B2 (cg-RX-API-DMAC7.html)
EP (1) EP3042343A2 (cg-RX-API-DMAC7.html)
JP (1) JP2016532216A (cg-RX-API-DMAC7.html)
KR (1) KR20160047581A (cg-RX-API-DMAC7.html)
CN (1) CN105518721B (cg-RX-API-DMAC7.html)
CA (1) CA2919718A1 (cg-RX-API-DMAC7.html)
WO (1) WO2015034640A2 (cg-RX-API-DMAC7.html)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016183522A1 (en) * 2015-05-14 2016-11-17 Thalchemy Corporation Neural sensor hub system
KR101806833B1 (ko) 2015-12-31 2017-12-11 인천대학교 산학협력단 인공 신경망의 희소 활동을 활용하는 동기 직접 회로의 소비 전력 절감 장치 및 방법
CN105956658A (zh) * 2016-04-29 2016-09-21 北京比特大陆科技有限公司 数据处理方法、数据处理装置及芯片
CN107545304A (zh) * 2017-09-16 2018-01-05 胡明建 一种根据网络需求改变激活函数人工神经元的设计方法
US11694066B2 (en) * 2017-10-17 2023-07-04 Xilinx, Inc. Machine learning runtime library for neural network acceleration
CN110515754B (zh) * 2018-05-22 2021-01-26 深圳云天励飞技术有限公司 神经网络处理器的调试系统及方法
US11694090B2 (en) 2019-04-10 2023-07-04 International Business Machines Corporation Debugging deep neural networks

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0439343A2 (en) * 1990-01-26 1991-07-31 International Business Machines Corporation Method of operating an expert system and computer systems therefor
US5459817A (en) * 1992-03-30 1995-10-17 Kabushiki Kaisha Toshiba Neural network with learning function based on simulated annealing and Monte-Carlo method
US6560592B1 (en) * 1998-03-19 2003-05-06 Micro Data Base Systems, Inc. Multi-model computer database storage system with integrated rule engine
CN1959653A (zh) * 2005-11-03 2007-05-09 国际商业机器公司 调试计算机程序的装置与方法
WO2013059703A1 (en) * 2011-10-19 2013-04-25 Qualcomm Incorporated Method and apparatus for neural learning of natural multi-spike trains in spiking neural networks

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2824936B1 (fr) 2001-05-16 2005-09-02 Schneider Automation Systeme de diagnostic predictif dans un automate programmable
JP4944368B2 (ja) * 2004-06-08 2012-05-30 キヤノン株式会社 マルチプロセッサシステム、デバッグ方法、及びプログラム
US7634761B2 (en) 2004-10-29 2009-12-15 Microsoft Corporation Breakpoint logging and constraint mechanisms for parallel computing systems
US20070130491A1 (en) 2005-12-06 2007-06-07 Mazumder Didarul A Error detection of digital logic circuits using hierarchical neural networks
US9665822B2 (en) 2010-06-30 2017-05-30 International Business Machines Corporation Canonical spiking neuron network for spatiotemporal associative memory
US8560474B2 (en) 2011-03-07 2013-10-15 Cisco Technology, Inc. System and method for providing adaptive manufacturing diagnoses in a circuit board environment
KR101838560B1 (ko) 2011-07-27 2018-03-15 삼성전자주식회사 뉴로모픽 칩에서 스파이크 이벤트를 송수신하는 송수신 장치 및 방법

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0439343A2 (en) * 1990-01-26 1991-07-31 International Business Machines Corporation Method of operating an expert system and computer systems therefor
US5459817A (en) * 1992-03-30 1995-10-17 Kabushiki Kaisha Toshiba Neural network with learning function based on simulated annealing and Monte-Carlo method
US6560592B1 (en) * 1998-03-19 2003-05-06 Micro Data Base Systems, Inc. Multi-model computer database storage system with integrated rule engine
CN1959653A (zh) * 2005-11-03 2007-05-09 国际商业机器公司 调试计算机程序的装置与方法
WO2013059703A1 (en) * 2011-10-19 2013-04-25 Qualcomm Incorporated Method and apparatus for neural learning of natural multi-spike trains in spiking neural networks

Also Published As

Publication number Publication date
US20150066826A1 (en) 2015-03-05
EP3042343A2 (en) 2016-07-13
JP2016532216A (ja) 2016-10-13
KR20160047581A (ko) 2016-05-02
WO2015034640A2 (en) 2015-03-12
US9710749B2 (en) 2017-07-18
WO2015034640A3 (en) 2015-05-14
CA2919718A1 (en) 2015-03-12
CN105518721A (zh) 2016-04-20

Similar Documents

Publication Publication Date Title
CN105934766B (zh) 用阴影网络来监视神经网络
CN105229675B (zh) 尖峰网络的高效硬件实现
CN106030622B (zh) 原位神经网络协同处理
CN105637541B (zh) 用于神经模拟器的共享存储器架构
CN105612492B (zh) 在人工神经系统中减少尖峰的方法、装置、设备及介质
US9959499B2 (en) Methods and apparatus for implementation of group tags for neural models
CN105830036A (zh) 神经看门狗
US9652711B2 (en) Analog signal reconstruction and recognition via sub-threshold modulation
CN106164940A (zh) 在尖峰神经网络中通过全局标量值来调制可塑性
CN105659262A (zh) 在尖峰神经网络中使用重放来实现突触学习
CN105518721A (zh) 用于在人工神经系统中实现断点确定单元的方法和装置
CN106133763B (zh) 可塑性突触管理
CN107077636A (zh) Cold神经元尖峰定时反向传播
CN105659261A (zh) 尖峰神经元网络中的拥塞避免
CN106068519A (zh) 用于共用神经元模型的高效实现的方法和装置
US20150213356A1 (en) Method for converting values into spikes
CN105659260B (zh) 动态地指派和检查突触延迟
US9418332B2 (en) Post ghost plasticity
CN105706121B (zh) 神经网络模型中的多普勒效应处理
CN105612536A (zh) 远程地控制和监视神经模型执行的方法和装置
US20150278684A1 (en) Time synchronization of spiking neuron models on multiple nodes

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant