CN106030621B - 用于空间目标选择的失衡式交叉抑制性机制 - Google Patents

用于空间目标选择的失衡式交叉抑制性机制 Download PDF

Info

Publication number
CN106030621B
CN106030621B CN201580009576.7A CN201580009576A CN106030621B CN 106030621 B CN106030621 B CN 106030621B CN 201580009576 A CN201580009576 A CN 201580009576A CN 106030621 B CN106030621 B CN 106030621B
Authority
CN
China
Prior art keywords
target
neuron
targets
robotic device
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
CN201580009576.7A
Other languages
English (en)
Chinese (zh)
Other versions
CN106030621A (zh
Inventor
N·G·劳
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 CN106030621A publication Critical patent/CN106030621A/zh
Application granted granted Critical
Publication of CN106030621B publication Critical patent/CN106030621B/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
    • 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
    • G06N3/06—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

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Computational Linguistics (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Neurology (AREA)
  • Image Analysis (AREA)
  • Feedback Control In General (AREA)
  • Image Processing (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
CN201580009576.7A 2014-02-21 2015-02-19 用于空间目标选择的失衡式交叉抑制性机制 Active CN106030621B (zh)

Applications Claiming Priority (7)

Application Number Priority Date Filing Date Title
US201461943231P 2014-02-21 2014-02-21
US201461943227P 2014-02-21 2014-02-21
US61/943,231 2014-02-21
US61/943,227 2014-02-21
US14/325,165 US20150242742A1 (en) 2014-02-21 2014-07-07 Imbalanced cross-inhibitory mechanism for spatial target selection
US14/325,165 2014-07-07
PCT/US2015/016685 WO2015127124A2 (en) 2014-02-21 2015-02-19 Imbalanced cross-inhibitory mechanism for spatial target selection

Publications (2)

Publication Number Publication Date
CN106030621A CN106030621A (zh) 2016-10-12
CN106030621B true CN106030621B (zh) 2019-04-16

Family

ID=52684672

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201580009576.7A Active CN106030621B (zh) 2014-02-21 2015-02-19 用于空间目标选择的失衡式交叉抑制性机制

Country Status (6)

Country Link
US (1) US20150242742A1 (enExample)
EP (1) EP3108412A2 (enExample)
JP (1) JP2017509979A (enExample)
CN (1) CN106030621B (enExample)
TW (1) TW201541373A (enExample)
WO (1) WO2015127124A2 (enExample)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10552734B2 (en) 2014-02-21 2020-02-04 Qualcomm Incorporated Dynamic spatial target selection

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102906767A (zh) * 2010-06-30 2013-01-30 国际商业机器公司 用于时空联合存储器的标准尖峰神经网络

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120271748A1 (en) * 2005-04-14 2012-10-25 Disalvo Dean F Engineering process for a real-time user-defined data collection, analysis, and optimization tool (dot)
KR100820723B1 (ko) * 2006-05-19 2008-04-10 인하대학교 산학협력단 은닉노드 목표값을 가진 2 개층 신경망을 이용한 분리 학습시스템 및 방법
US9281689B2 (en) * 2011-06-08 2016-03-08 General Electric Technology Gmbh Load phase balancing at multiple tiers of a multi-tier hierarchical intelligent power distribution grid
US9092735B2 (en) * 2011-09-21 2015-07-28 Qualcomm Incorporated Method and apparatus for structural delay plasticity in spiking neural networks
US9367797B2 (en) * 2012-02-08 2016-06-14 Jason Frank Hunzinger Methods and apparatus for spiking neural computation
US9460382B2 (en) * 2013-12-23 2016-10-04 Qualcomm Incorporated Neural watchdog

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102906767A (zh) * 2010-06-30 2013-01-30 国际商业机器公司 用于时空联合存储器的标准尖峰神经网络

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
New technologies for testing a model of cricket phonotaxis on an outdoor robot;Richard Reeve等;《Robotics and Autonomous Systems》;20050106;第2.2.2-2.2.3节，图2 *

Also Published As

Publication number Publication date
CN106030621A (zh) 2016-10-12
WO2015127124A2 (en) 2015-08-27
EP3108412A2 (en) 2016-12-28
JP2017509979A (ja) 2017-04-06
TW201541373A (zh) 2015-11-01
WO2015127124A3 (en) 2015-11-05
US20150242742A1 (en) 2015-08-27

Similar Documents

Publication Publication Date Title
CN106030620B (zh) 用于随机尖峰贝叶斯网络的基于事件的推断和学习
CN105637541A (zh) 用于神经模拟器的共享存储器架构
CN106030622B (zh) 原位神经网络协同处理
CN106796667B (zh) 动态空间目标选择
US10339447B2 (en) Configuring sparse neuronal networks
CN105981055A (zh) 神经网络对当前计算资源的自适应
CN106663222A (zh) 神经网络中的分解卷积操作
Robinson et al. Dynamic reinforcement driven error propagation networks with application to game playing
TW201602807A (zh) Ｃｏｌｄ神經元尖峰時序反向傳播
JP2017519268A (ja) スパイキングニューラルネットワークにおけるグローバルスカラ値によって可塑性を調節すること
JP6133517B2 (ja) 座標変換のための位相コーディング
Chen et al. Trakdis: A transformer-based knowledge distillation approach for visual reinforcement learning with application to cloth manipulation
CN105706121B (zh) 神经网络模型中的多普勒效应处理
CN105659260B (zh) 动态地指派和检查突触延迟
CN106030621B (zh) 用于空间目标选择的失衡式交叉抑制性机制
KR20160132850A (ko) 뉴로모픽 모델 개발을 위한 콘텍스트 실시간 피드백
Wang et al. Toward a new three layer neural network with dynamical optimal training performance
Ravi et al. Online multiple-model approach to prediction for financial markets
CN107665387A (zh) 量子金融预测系统以及采用该预测系统的量子金融系统

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