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ON THE APPROXIMATION BY RBF NEURAL NETWORKS WITH TRANSLATIONS
Proceedings of the Institute of Mathematics and Mechanics National Academy of Sciences of Azerbaijanopenaire +1 more source
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Accelerated gradient algorithm for RBF neural network
Neurocomputing, 2021Abstract Gradient-based algorithms are commonly used for training radial basis function neural network (RBFNN). However, one of the challenges in the training process is determining how to avoid vanishing gradient. To solve this problem, an accelerated gradient algorithm (AGA) is designed to improve the learning performance of RBFNN in this paper ...
Hong-Gui Han, Miao-Li Ma, Jun-Fei Qiao
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An adiabatic neural network for RBF approximation
Neural Computing & Applications, 1994Numerous studies have addressed nonlinear functional approximation by multilayer perceptrons (MLPs) and RBF networks as a special case of the more general mapping problem. The performance of both these supervised network models intimately depends on the efficiency of their learning process.
Bart Truyen +2 more
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Adaptive Computation Algorithm for RBF Neural Network
IEEE Transactions on Neural Networks and Learning Systems, 2012A novel learning algorithm is proposed for nonlinear modelling and identification using radial basis function neural networks. The proposed method simplifies neural network training through the use of an adaptive computation algorithm (ACA). In addition, the convergence of the ACA is analyzed by the Lyapunov criterion. The proposed algorithm offers two
Hong-Gui Han, Junfei Qiao 0001
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2001
Determining the parameters of a Radial Basis Function Neural Nerwork (number of neurons, and their respective centers and radii) is often done by hand, or based in methods highly dependent on initial values. In this work, Evolutionary Algorithms are used to automatically build a RBF NN that solves a specified problem.
Víctor Manuel Rivas Santos +2 more
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Determining the parameters of a Radial Basis Function Neural Nerwork (number of neurons, and their respective centers and radii) is often done by hand, or based in methods highly dependent on initial values. In this work, Evolutionary Algorithms are used to automatically build a RBF NN that solves a specified problem.
Víctor Manuel Rivas Santos +2 more
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Recognition of pump state by RBF neural network
2005 IEEE International Conference on Robotics and Biomimetics - ROBIO, 2005The arising of neural network theory is a breakthrough from machine processing to man's thinking mode. On the basis of the traditional BP and RBF neural network, this article applies a new algorithm user-defined step radial basis function to recognize ZYB03-60 vacuum air press pump. It turns out that the algorithm can train studying-speed faster and it
Jimei Wu, Qiumin Wu
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RBF neural network controller based on OLSSVR
2013 9th Asian Control Conference (ASCC), 2013In this paper, a predictive adaptation method based on Online Least Square Support Vector Regression (OLSVR) for a RBF controller has been proposed. System Jacobian is approximated via Online LSSVR model of the system to tune RBF controller. The parameters of the controller have been tuned depending on K-step ahead future behavior of the system to ...
Kemal Ucak, Gülay Öke Günel
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