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检索条件"主题词=Backpropagation Algorithms"
1892 条 记 录,以下是1831-1840 订阅
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Comparison of TDNN training algorithms in brain machine interfaces
Comparison of TDNN training algorithms in brain machine inte...
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International Joint Conference on Neural Networks (IJCNN)
作者: Yiwen Wang Sung-Phil Kim J.C. Principe Computational NeuroEngineering Laboratory University of Florida Gainesville FL USA
Linear or non-linear models are used in brain machine interfaces (BIMIs) to map the neural activity to the associated behavior, typically the primate's hand position. Linear models assume a linear relationship bet... 详细信息
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Neural networks for sensor fusion in remote sensing
Neural networks for sensor fusion in remote sensing
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International Joint Conference on Neural Networks (IJCNN)
作者: H. Pasika S. Haykin E. Clothiaux R. Stewart McMaster University Hamilton ONT Canada Pennslyvania State University PA USA Environment Canada Downsview ONT Canada
Cloud base height is a continuous variable that falls within the range of zero to fourteen kilometers and is useful for understanding the Earth's radiation budget. Advances in LIDAR (laser radar) technology have p... 详细信息
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An adaptive and fully sparse training approach for multilayer perceptrons
An adaptive and fully sparse training approach for multilaye...
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International Conference on Neural Networks
作者: Fang Wang Q.J. Zhang Department of Electronics Carleton University Ottawa Canada
An adaptive and fully sparse backpropagation training approach is proposed in this paper. The technique speeds up training by combining a sparse optimization concept with neural network training. The sparse phenomenon... 详细信息
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A learning machine for resource-limited adaptive hardware
A learning machine for resource-limited adaptive hardware
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NASA/ESA Conference on Adaptive Hardware and Systems (AHS)
作者: Davide Anguita Alessandro Ghio Stefano Pischiutta DIBE-Department of Biophysical and Electronic Engineering University of Genoa Genoa Italy
Machine learning algorithms allow to create highly adaptable systems, since their functionality only depends on the features of the inputs and the coefficients found during the training stage. In this paper, we presen... 详细信息
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A parameter estimation approach to artificial neural network weight selection for nonlinear system identification
A parameter estimation approach to artificial neural network...
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IEEE Conference on Control Technology and Applications (CCTA)
作者: T.L. Ruchti R.H. Brown J.J. Garside Department of Electrical and Computer Engineering Marquette University Milwaukee WI USA
A unified framework for artificial neural network (ANN) training algorithms applied to nonlinear system identification based on considering weight selection as a parameter estimation problem is presented. Three existi... 详细信息
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Optimizing Neural Net based Predictive Control
Optimizing Neural Net based Predictive Control
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American Control Conference (ACC)
作者: Jean Saint Donat Naveen Bhat Thomas J. McAvoy Department of Chemical Engineering University of Maryland College Park MD USA
Neural networks hold great promise for application in the general area of process control. This paper focuses on using a backpropagation network in an optimization based model predictive control scheme. Since analytic... 详细信息
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Minimizing Distribution Cost of Distributed Neural Networks in Wireless Sensor Networks
Minimizing Distribution Cost of Distributed Neural Networks ...
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IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference
作者: Peng Guan Xiaolin Li Scalable Software Systems Laboratory Department of Computer Science Oklahoma State University Stillwater OK USA
This paper presents a novel study on how to distribute neural networks in a wireless sensor networks (WSNs) such that the energy consumption is minimized while improving the accuracy and training efficiency. Artificia... 详细信息
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On the evaluation of relevance learning by a multi-layer perceptron
On the evaluation of relevance learning by a multi-layer per...
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International Joint Conference on Neural Networks (IJCNN)
作者: K. Suzuki S. Hashimoto Department of Intelligent Interaction Technologies University of Tsukuba Tsukuba Japan Department of Applied Physics Waseda University Tokyo Japan
In this paper, we introduce a novel method of relevance learning by a multi-layer perceptron. The relevance learning is regarded as learning from the relationship among two or more outputs of the network. The learning... 详细信息
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Isolated speech recognition using artificial neural networks
Isolated speech recognition using artificial neural networks
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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
作者: P.D. Polur Ruobing Zhou Jun Yang F. Adnani R.S. Hobson Department of Biomedical Engineering Virginia Commonwealth University Virginia USA Department of Electrical Engineering Virginia Commonwealth University Virginia USA
In this project artificial neural networks are used as research tool to accomplish automated speech recognition of normal speech. A small size vocabulary containing the words YES and NO is chosen. Spectral features us... 详细信息
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Edge representation and recognition using neural networks
Edge representation and recognition using neural networks
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IEEE International Symposium on Industrial Electronics (ISIE)
作者: Ohjae Kwon Chulhee Lee Department Electrical and Electronic Engineering Yonsei University Seoul South Korea
In this paper, we propose a new approach to represent and recognize edges of objects using multilayer feedforward neural networks. First, we show how then edge of an object can be represented by neural networks. This ... 详细信息
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