Proceedings ArticleDOI
Research of neural network algorithm based on FA and RBF
Shifei Ding,Weikuan Jia,Chunyang Su,Jinrong Chen +3 more
- Vol. 7
Reads0
Chats0
TLDR
This paper proposes a radial basis function (RBF) neural network algorithm based on factor analysis (FA- RBF) with the architecture feature of RBF network when the data are high-dimensional and complex, and compares it with the RBF neural network algorithms based on principal component analysis (PCA-RBF).Abstract:
This paper proposes a radial basis function (RBF) neural network algorithm based on factor analysis (FA-RBF) with the architecture feature of RBF network when the data are high-dimensional and complex. By reducing the feature dimension of the original data, FA-RBF algorithm regards the data after dimension reduction as the inputs of the RBF network, and then trains and simulates the network. The algorithm obviously simplifies the network architecture. By analyzing an example, the results show when the algorithm's predicted precision is not reduced, the convergence velocity is improved, the running time is saved and the error of the predicted value is reduced. In order to test and verify the validity of the new algorithm, we compare it with the RBF neural network algorithm based on principal component analysis (PCA-RBF), the predicted results of FA-RBF algorithm are better than the results of RBF and PCA-RBF algorithm.read more
Citations
More filters
Journal ArticleDOI
Radial basis function neural networks: a topical state-of-the-artsurvey
TL;DR: The overall algorithmic development of RBF networks by giving special focus on their learning methods, novel kernels, and fine tuning of kernel parameters have been discussed and the recent research work on optimization of multi-criterions inRBF networks is considered.
Journal ArticleDOI
A new optimized GA-RBF neural network algorithm
TL;DR: A new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm) is proposed, which uses genetic algorithm to optimize the weights and structure of RBF Neural network; it chooses new ways of hybrid encoding and optimizing simultaneously.
Journal ArticleDOI
Neural Tool Condition Estimation in The Grinding of Advanced Ceramics
Mauricio Eiji Nakai,Hildo Guillardi Junior,Paulo Roberto de Aguiar,Eduardo Carlos Bianchi,Danilo Hernane Spatti +4 more
TL;DR: In this paper, the authors used neural networks to estimate tool wear during the grinding of advanced ceramics using data collected from a surface grinding machine with tangential diamond wheel and alumina ceramic test specimens, in three cutting configurations.
Proceedings ArticleDOI
Image compression: Wavelet transform using radial basis function (RBF) neural network
G Boopathi,S. Arockiasamy +1 more
TL;DR: A combined approach of image compression based on vector quantization and wavelet transform is proposed using RBF neural network, which will be very helpful for medical imaging, criminal investigation where high precision reconstructed image is required.
Journal ArticleDOI
Using RBF networks for detection and prediction of flip chip with missing bumps
TL;DR: In this paper, a radial basis function (RBF) network was proposed to detect and predict missing solder bumps, a typical defect in flip chips, which can be used for defect inspection in microelectronic packaging industry.
References
More filters
Journal ArticleDOI
Learning representations by back-propagating errors
TL;DR: Back-propagation repeatedly adjusts the weights of the connections in the network so as to minimize a measure of the difference between the actual output vector of the net and the desired output vector, which helps to represent important features of the task domain.
Journal ArticleDOI
A logical calculus of the ideas immanent in nervous activity
Warren S. McCulloch,Walter Pitts +1 more
TL;DR: In this article, it is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under another and gives the same results, although perhaps not in the same time.
Book
Applied Multivariate Statistical Analysis
R. A. Johnson,Dean W. Wichern +1 more
TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
Journal ArticleDOI
Applied Multivariate Statistical Analysis.
TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.