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检索条件"主题词=Learning algorithm"
745 条 记 录,以下是11-20 订阅
排序:
learning algorithm Designs for Biological Neural Networks
Learning Algorithm Designs for Biological Neural Networks
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作者: Zeng, Yuan Lehigh University
学位级别:Ph.D., Doctor of Philosophy
Artificial neural networks have shown great success in solving real-world problems in recent years. Nowadays, most of the widely used neural network algorithms are running on silicon-based computers, where the resourc... 详细信息
来源: 评论
A learning algorithm for rate selection in real-time wireless LANs
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COMPUTER NETWORKS 2017年 126卷 114-124页
作者: Luvisotto, Michele Tramarin, Federico Vitturi, Stefano Univ Padua Dept Informat Engn Via Gradenigo 6-B I-35131 Padua Italy Natl Res Council Italy CNR IEIIT Via Gradenigo 6-B I-35131 Padua Italy
To achieve a real-time behavior in wireless communication systems, the multi-rate support (MRS) provided by the IEEE 802.11 Wireless LAN standard may reveal particularly advantageous. Unfortunately, the most widesprea... 详细信息
来源: 评论
learning algorithm for Linguistic Information Feedback-based Dynamical Fuzzy System (LIFDFS)
Learning algorithm for Linguistic Information Feedback-based...
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IEEE International Conference on Systems, Man and Cybernetics
作者: Gao, XZ Ovaska, SJ Wang, X Aalto Univ Inst Intelligent Power Elect FIN-02150 Espoo Finland
In this paper the Linguistic Information Feedback-based Dynamical Fuzzy System (LIFDFS) proposed earlier by the authors is first introduced. The principles of alpha-level sets and Backpropagation Through Time (BTT) ar... 详细信息
来源: 评论
Multigradient: A new neural network learning algorithm for pattern classification
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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2001年 第5期39卷 986-993页
作者: Go, J Han, G Kim, H Lee, C Yonsei Univ Dept Elect & Elect Engn Seoul 120749 South Korea
In this paper, we propose a new learning algorithm for multilayer feedforward neural networks, which converges faster and achieves a better classification accuracy than the conventional backpropagation learning algori... 详细信息
来源: 评论
A novel material removal prediction method based on acoustic sensing and ensemble XGBoost learning algorithm for robotic belt grinding of Inconel 718
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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2019年 第1-4期105卷 217-232页
作者: Gao, Kaiyuan Chen, Huabin Zhang, Xiaoqiang Ren, XuKai Chen, Junqi Chen, Xiaoqi Shanghai Jiao Tong Univ Sch Mat Sci & Engn Shanghai Key Lab Mat Laser Proc & Modificat Shanghai 200240 Peoples R China Swinbume Univ Technol Fac Sci Engn & Technol Mfg Futures Res Inst Hawthorn Vic Australia
High-performance component manufacturing has increasing needs of robotic grinding process that can achieve accurate material removal. This article proposes a novel material removal model for robotic belt grinding of I... 详细信息
来源: 评论
A learning algorithm for Risk-Sensitive Cost
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MATHEMATICS OF OPERATIONS RESEARCH 2008年 第4期33卷 880-898页
作者: Basu, Arnab Bhattacharyya, Tirthankar Borkar, Vivek S. Indian Inst Management Bangalore Quantitat Methods & Informat Syst Area Bangalore 560076 Karnataka India Indian Inst Sci Dept Math Bangalore 560012 Karnataka India Tata Inst Fundamental Res Sch Technol & Comp Sci Bombay 400005 Maharashtra India
A linear function approximation-based reinforcement learning algorithm is proposed for Markov decision processes with infinite horizon risk-sensitive cost. Its convergence is proved using the "o.d.e. method"... 详细信息
来源: 评论
Leave-two-out stability of ontology learning algorithm
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CHAOS SOLITONS & FRACTALS 2016年 89卷 322-327页
作者: Wu, Jianzhang Yu, Xiao Zhu, Linli Gao, Wei Southeast Univ Sch Comp Sci & Engineer Nanjing 210096 Jiangsu Peoples R China Southeast Univ Sch Continuing Educ Nanjing 210096 Jiangsu Peoples R China Jiangsu Univ Technol Sch Comp Engn Changzhou 213001 Jiangsu Peoples R China Yunnan Normal Univ Sch Informat Sci & Technol Kunming 650500 Peoples R China
Ontology is a semantic analysis and calculation model, which has been applied to many subjects. Ontology similarity calculation and ontology mapping are employed as machine learning approaches. The purpose of this pap... 详细信息
来源: 评论
A New learning algorithm for Optimal Stopping
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DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS 2009年 第1期19卷 91-113页
作者: Borkar, Vivek S. Pinto, Jervis Prabhu, Tarun Tata Inst Fundamental Res Mumbai 400005 Maharashtra India St Francis Inst Technol Mumbai 400103 Maharashtra India
A linear programming formulation of the optimal stopping problem for Markov decision processes is approximated using linear function approximation. Using this formulation, a reinforcement learning scheme based on a pr... 详细信息
来源: 评论
A STOCHASTIC REINFORCEMENT learning algorithm FOR learning REAL-VALUED FUNCTIONS
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NEURAL NETWORKS 1990年 第6期3卷 671-692页
作者: GULLAPALLI, V Department of Computer and Information Science University of Massachusetts USA
Most of the research in reinforcement learning has been on problems with discrete action spaces. However, many control problems require the application of continuous control signals. In this paper, we present a stocha... 详细信息
来源: 评论
A new supervised learning algorithm for multilayered and interconnected neural networks
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IEEE TRANSACTIONS ON NEURAL NETWORKS 2000年 第1期11卷 36-46页
作者: Yamamoto, Y Nikiforuk, PN Tottori Univ Fac Engn Dept Informat & Knowledge Engn Tottori 6808552 Japan Univ Saskatchewan Coll Engn Dept Mech Engn Saskatoon SK S7N 5A9 Canada
A new learning algorithm is presented for supervised learning of multilayered and interconnected neural networks without using a gradient method. First, fictitious teacher signals for the outputs of each hidden unit a... 详细信息
来源: 评论