CN105580031B - 在多维范围上对包括可分离子系统的系统的评估 - Google Patents

在多维范围上对包括可分离子系统的系统的评估 Download PDF

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CN105580031B
CN105580031B CN201480052142.0A CN201480052142A CN105580031B CN 105580031 B CN105580031 B CN 105580031B CN 201480052142 A CN201480052142 A CN 201480052142A CN 105580031 B CN105580031 B CN 105580031B
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interconnected neurons
neurons
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CN105580031A (zh
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M·坎伯斯
C·M·维任斯基
B·F·贝哈巴迪
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Qualcomm Inc
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    • 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
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    • G06N3/0495—Quantised networks; Sparse networks; Compressed networks
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    • 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
    • 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
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    • G06N3/0985—Hyperparameter optimisation; Meta-learning; Learning-to-learn
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    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • 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
    • 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
    • G06N3/105—Shells for specifying net layout
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    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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  • Engineering & Computer Science (AREA)
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CN201480052142.0A 2013-10-28 2014-10-17 在多维范围上对包括可分离子系统的系统的评估 Expired - Fee Related CN105580031B (zh)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US14/065,388 US9721204B2 (en) 2013-10-28 2013-10-28 Evaluation of a system including separable sub-systems over a multidimensional range
US14/065,388 2013-10-28
PCT/US2014/061220 WO2015065738A2 (en) 2013-10-28 2014-10-17 Evaluation of a system including separable sub-systems over a multidimensional range

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CN105580031A CN105580031A (zh) 2016-05-11
CN105580031B true CN105580031B (zh) 2018-01-16

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US (1) US9721204B2 (enExample)
EP (1) EP3063707A2 (enExample)
JP (1) JP2016538633A (enExample)
KR (1) KR20160076531A (enExample)
CN (1) CN105580031B (enExample)
CA (1) CA2926649A1 (enExample)
TW (1) TW201525883A (enExample)
WO (1) WO2015065738A2 (enExample)

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US10515312B1 (en) * 2015-12-30 2019-12-24 Amazon Technologies, Inc. Neural network model compaction using selective unit removal
CN106203621B (zh) * 2016-07-11 2019-04-30 北京深鉴智能科技有限公司 用于卷积神经网络计算的处理器
US11315018B2 (en) 2016-10-21 2022-04-26 Nvidia Corporation Systems and methods for pruning neural networks for resource efficient inference
EP3340129B1 (en) * 2016-12-21 2019-01-30 Axis AB Artificial neural network class-based pruning
US11188820B2 (en) * 2017-09-08 2021-11-30 International Business Machines Corporation Deep neural network performance analysis on shared memory accelerator systems
CN111587436B (zh) * 2018-01-17 2025-02-28 昕诺飞控股有限公司 用于使用神经网络进行对象辨识的系统和方法
CN110543933B (zh) * 2019-08-12 2022-10-21 北京大学 基于flash存算阵列的脉冲型卷积神经网络
CN110570616B (zh) * 2019-09-10 2020-09-25 淮阴工学院 一种基于物联网的多点火灾预警系统
DE102019214436A1 (de) * 2019-09-23 2021-03-25 Robert Bosch Gmbh Verfahren, Vorrichtung und Computerprogramm zum Betreiben eines künstlichen neuronalen Netzes
KR20210115863A (ko) 2020-03-16 2021-09-27 삼성전자주식회사 뉴럴 네트워크 모델을 위한 병렬 처리 방법 및 장치
KR102624947B1 (ko) * 2023-11-28 2024-01-15 주식회사 티알씨일렉트릭 전동기 역설계 장치 및 방법
CN119227881B (zh) * 2024-09-12 2025-05-06 西安电子科技大学 引入偏离系数实现耦合模型全域连续相似预测的方法

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CN101893541A (zh) * 2010-06-09 2010-11-24 哈尔滨工业大学 建立纤维增强树脂基复合材料孔隙问题的表征与评价模型的方法

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US9721204B2 (en) 2017-08-01
TW201525883A (zh) 2015-07-01
JP2016538633A (ja) 2016-12-08
CA2926649A1 (en) 2015-05-07
WO2015065738A2 (en) 2015-05-07
CN105580031A (zh) 2016-05-11
WO2015065738A3 (en) 2015-07-09
US20150120632A1 (en) 2015-04-30
EP3063707A2 (en) 2016-09-07
KR20160076531A (ko) 2016-06-30

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