机构

• 自动化研究所 [5]
• 计算技术研究所 [2]
• 长春光学精密机械与物... [2]
• 西安光学精密机械研究... [1]
• 国家授时中心 [1]

采集方式

• OAI收割 [11]

内容类型

• 期刊论文 [9]
• 会议论文 [2]

发表日期

• 2023 [1]
• 2022 [2]
• 2021 [1]
• 2020 [1]
• 2017 [3]
• 2013 [1]
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学科主题

• astronomy ... [1]
• geoscience... [1]
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浏览/检索结果: 共11条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Network Pruning for Bit-Serial Accelerators 期刊论文  OAI收割 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2023, 卷号: 42, 期号: 5, 页码: 1597-1609 作者:  Zhao, Xiandong;  Wang, Ying;  Liu, Cheng;  Shi, Cong;  Tu, Kaijie   |  收藏  |  浏览/下载：12/0  |  提交时间：2023/12/04 AI accelerators  neural networks (NNs)  NN compression   Rethinking Pretraining as a Bridge From ANNs to SNNs 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 14 作者:  Lin, Yihan   |  收藏  |  浏览/下载：26/0  |  提交时间：2023/03/20 Training  Task analysis  Neurons  Pipelines  Artificial neural networks  Feature extraction  Transfer learning  Event-driven dataset  neural network (NN) analysis  pretraining technique  spiking NN (SNN)  transfer learning   Finite-Time Stability Control of Uncertain Nonlinear Systems With Self-Limiting Control Terms 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 6 作者:  Zhu, Jiaming;  Yang, Yuequan;  Zhang, Tianping;  Cao, Zhiqiang   |  收藏  |  浏览/下载：27/0  |  提交时间：2022/06/06 Artificial neural networks  Nonlinear systems  Control systems  Adaptive systems  Backstepping  Biological neural networks  Trajectory  Backstepping  dynamic surface control (DSC)  finite-time tracking  neural network (NN)  self-limiting term   Adaptive Neural Control of Nonlinear Nonstrict Feedback Systems With Full-State Constraints: A Novel Nonlinear Mapping Method 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 9 作者:  Zhang, Jiaming;  Niu, Ben;  Wang, Ding;  Wang, Huanqing;  Duan, Peiyong   |  收藏  |  浏览/下载：28/0  |  提交时间：2022/01/27 Nonlinear systems  Artificial neural networks  Design methodology  Adaptive control  Time-varying systems  Fuzzy logic  Backstepping  Asymptotic tracking control  neural networks (NN)  nonlinear mapping (NM)  nonstrict feedback structure  time-varying full-state constraints  uncertain nonlinear system   Self-Aware Neural Network Systems: A Survey and New Perspective 期刊论文  OAI收割 PROCEEDINGS OF THE IEEE, 2020, 卷号: 108, 期号: 7, 页码: 1047-1067 作者:  Du, Zidong;  Guo, Qi;  Zhao, Yongwei;  Chen, Yunji;  Xu, Zhiwei   |  收藏  |  浏览/下载：37/0  |  提交时间：2020/12/10 Artificial neural networks  Neurons  Self-aware  Monitoring  Sensors  Program processors  Logic gates  Self-aware neural network (NN) processors   Adaptive dynamic programming for robust neural control of unknown continuous-time non-linear systems 期刊论文  OAI收割 IET CONTROL THEORY AND APPLICATIONS, 2017, 卷号: 11, 期号: 14, 页码: 2307-2316 作者:  Yang, Xiong;  He, Haibo;  Liu, Derong;  Zhu, Yuanheng   |  收藏  |  浏览/下载：36/0  |  提交时间：2017/09/13 Dynamic Programming  Robust Control  Neurocontrollers  Continuous Time Systems  Control System Synthesis  Nonlinear Control Systems  Optimal Control  Function Approximation  Monte Carlo Methods  Closed Loop Systems  Asymptotic Stability  Adaptive Dynamic Programming  Robust Neural Control Design  Unknown Continuous-time Nonlinear Systems  Ct Nonlinear Systems  Adp-based Robust Neural Control Scheme  Robust Nonlinear Control Problem  Nonlinear Optimal Control Problem  Nominal System  Adp Algorithm  Actor-critic Dual Networks  Control Policy Approximation  Value Function Approximation  Actor Neural Network Weights  Critic Nn Weights  Monte Carlo Integration Method  Closed-loop System  Asymptotically Stability   Short-term prediction of UT1-UTC by combination of the grey model and neural networks 期刊论文  OAI收割 advances in space research, 2017, 卷号: 59, 期号: 2, 页码: 524-531 作者:  Lei, Yu;  Guo, Min;  Hu, Dan-dan;  Cai, Hong-bing;  Zhao, Dan-ning 收藏  |  浏览/下载：41/0  |  提交时间：2017/03/15 UT1-UTC  Prediction  Grey model  Neural Networks (NN)   Short-term prediction of UT1-UTC by combination of the grey model and neural networks 期刊论文  OAI收割 ADVANCES IN SPACE RESEARCH, 2017, 卷号: 59, 期号: 2, 页码: 524-531 作者:  Lei, Yu;  Guo, Min;  Hu, Dan-dan;  Cai, Hong-bing;  Zhao, Dan-ning   |  收藏  |  浏览/下载：11/0  |  提交时间：2021/11/29 UT1-UTC  Prediction  Grey model  Neural Networks (NN)   Neural-network-based online optimal control for uncertain non-linear continuous-time systems with control constraints 期刊论文  OAI收割 IET CONTROL THEORY AND APPLICATIONS, 2013, 卷号: 7, 期号: 17, 页码: 2037-2047 作者:  Yang, Xiong;  Liu, Derong;  Huang, Yuzhu 收藏  |  浏览/下载：32/0  |  提交时间：2015/08/12 adaptive control  approximation theory  closed loop systems  continuous time systems  Lyapunov methods  neurocontrollers  nonlinear control systems  optimal control  robust control  uncertain systems  neural network-based online adaptive optimal control  uncertain nonlinear continuous-time systems  control constraints  infinite-horizon optimal control problem  control policy  saturation constraints  identifier-critic architecture  Hamilton-Jacobi-Bellman equation approximation  uncertain system dynamics  critic NN  action-critic dual networks  reinforcement learning  identifier NN  policy iteration  LyapunovaEuros direct method  closed loop system stability   Neural network based online traffic signal controller design with reinforcement training (EI CONFERENCE) 会议论文  OAI收割 14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011, October 5, 2011 - October 7, 2011, Washington, DC, United states Dai Y.; Hu J.; Zhao D.; Zhu F. 收藏  |  浏览/下载：29/0  |  提交时间：2013/03/25 Traffic congestion leads to problems like delays  decreasing flow rate  and higher fuel consumption. Consequently  keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus  computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper  a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions. 2011 IEEE.