Radial Basis Function Network
Mostrando 13-20 de 20 artigos, teses e dissertações.
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13. Identificação de sistemas não-lineares multivariáveis usando redes neurais perceptron multicamadas e função de base radial
The identification of multivariable nonlinear dynamic systems is an important area in Engineering. This dissertation presents a methodology based on artificial neural networks for identification of nonlinear system with some inputs and outputs. This study it is mainly motivated by artificial neural networks to present potentialities for identification of non
Publicado em: 2005
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14. Aplicação de alguns modelos quimiométricos à espectroscopia de fluorescência de raios-X de energia dispersiva
The objective of this work was to accomplish the simultaneous determination of some chemical elements by Energy Dispersive X-ray Fluorescence (EDXRF) Spectroscopy through multivariate calibration in several sample types. The multivariate calibration models were: Back Propagation neural network, Levemberg-Marquardt neural network and Radial Basis Function neu
Química Nova. Publicado em: 2002-11
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15. Adaptive control using a hybrid-neural model: application to a polymerisation reactor
This work presents the use of a hybrid-neural model for predictive control of a plug flow polymerisation reactor. The hybrid-neural model (HNM) is based on fundamental conservation laws associated with a neural network (NN) used to model the uncertain parameters. By simulations, the performance of this approach was studied for a peroxide-initiated styrene tu
Brazilian Journal of Chemical Engineering. Publicado em: 2001-03
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16. Predição não-linear de series temporais usando redes neurais RBF por decomposição em componentes principais
This thesis proposes a new technique for non-linear time series forecasting based upon Radial Basis Function Neural Networks and the Karhunen-Loeve Transform. A significant performance improvement is obtained with the novel technique in comparison with usual prediction methods. By obtaining the neural network centers from the data set sub-spaces - or data se
Publicado em: 2001
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17. Equalização não-linear de canais de comunicação. / Non-linear equalization on communication channels.
É investigado o uso de redes neurais aplicadas à equalização de canais de comunicação, sendo consideradas três tipos de redes: MLP (Multilayer Perceptron), RBF (Radial Basis Function) e RNN (Recurrent Neural Network). Os equalizadores não-lineares baseados nestas redes foram comparados com o equalizador linear transversal e com os equalizadores ótim
Publicado em: 2001
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18. Fault detection and diagnosis in robotic manipulators via artificial neural networks. / Detecção e diagnóstico de falhas em robôs manipuladores via redes neurais artificiais.
In this work, a new approach for fault detection and diagnosis in robotic manipulators is presented. A faulty robot could cause serious damages and put in risk the people involved. Usually, researchers have proposed fault detection and diagnosis schemes based on the mathematical model of the system. However, modeling errors could obscure the fault effects an
Publicado em: 1999
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19. Identification of Phytoplankton from Flow Cytometry Data by Using Radial Basis Function Neural Networks
We describe here the application of a type of artificial neural network, the Gaussian radial basis function (RBF) network, in the identification of a large number of phytoplankton strains from their 11-dimensional flow cytometric characteristics measured by the European Optical Plankton Analyser instrument. The effect of network parameters on optimization is
American Society for Microbiology.
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20. Comparison of Statistical Methods for Identification of Streptococcus thermophilus, Enterococcus faecalis, and Enterococcus faecium from Randomly Amplified Polymorphic DNA Patterns
Thermophilic streptococci play an important role in the manufacture of many European cheeses, and a rapid and reliable method for their identification is needed. Randomly amplified polymorphic DNA (RAPD) PCR (RAPD-PCR) with two different primers coupled to hierarchical cluster analysis has proven to be a powerful tool for the classification and typing of Str
American Society for Microbiology.