Radial Basis Function Networks
Mostrando 1-12 de 24 artigos, teses e dissertações.
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1. Hybrid Geoid Model: Theory and Application in Brazil
Determination of the ellipsoidal height by Global Navigation Satellite Systems (GNSS) is becoming better known and used for purposes of leveling with the aid of geoid models. However, the disadvantage of this method is the quality of the geoid models, which degrade heights and limit the application of the method. In order to provide better quality in transfo
An. Acad. Bras. Ciênc.. Publicado em: 2017-09
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2. Predicting the dynamic material constants of Mooney-Rivlin model in broad frequency range for elastomeric components
In this paper, dynamic material constants of 2-parameter Mooney-Rivlin model for elastomeric components are identified in broad frequency range. To consider more practical case, an elastomeric engine mount is used as the case study. Finite element model updating technique using Radial Basis Function neural networks is implemented to predict the dynamic mater
Lat. Am. j. solids struct.. Publicado em: 2014
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3. Design of multiple function antenna array using radial basis function neural network
A novel approach to design Multiple Function Antenna (MFA) arrays using Artificial Neural Networks is suggested. A planar array with uniform current excitations which can generate different beam widths and gains is designed using Artificial Neural Networks. The desired beam width, gain and number of elements are given as input to the neural network. The outp
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2013-06
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4. A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened steel turning
The use of artificial neural networks for prediction in hard turning has received considerable attention in literature. An often quoted drawback of ANNs is the lack of a systematic way for the design of high performance networks. This study presents a DOE based approach for the design of ANNs of Radial Basis Function (RBF) architecture applied to surface rou
Journal of the Brazilian Society of Mechanical Sciences and Engineering. Publicado em: 2010-12
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5. Synergistic control of forearm based on accelerometer data and artificial neural networks
In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural ne
Brazilian Journal of Medical and Biological Research. Publicado em: 30/04/2008
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6. Aplicação de redes neurais artificiais na ciência e tecnologia de alimentos : estudo de casos
Artificial Neural Networks (ANNs) are a non algorithm computing method capable of solving complex problems, getting better results than mathematical methods. The artificial neural networks has been used in many areas of technology and food science, most of them in classification problems, prediction, pattern recognition and control. This study approach two d
Publicado em: 2008
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7. Concurrent blind channel equalization with phase transmittance rbf neural networks
This paper presents a new complex valued radial basis function (RBF) neural network (NN) with phase transmittance between the input nodes and output, which makes it suitable for channel equalization on quadrature digital modulation systems. The new Phase Transmittance RBFNN (PTRBFNN) differs from the classical complex valued RBFNN in that it does not strictl
Journal of the Brazilian Computer Society. Publicado em: 2007-03
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8. Recuperação de perfis de temperatura e umidade da atmosfera a partir de dados de satélite - abordagens por redes neurais artificiais e implementação em hardware / Atmospheric temperature and humidity retrieval from satellite data - artificial neural networks and hardware implementation approaches
This thesis presents Artificial Neural Networks for inverse problem solution to recover atmospheric temperature and moisture profiles from satellite data. The Artificial Neural Networks are presented as alternative methods in the solution of inverse problems in the atmospheric data retrieval, considered ill-posed problems and requiring advanced numerical tec
Publicado em: 2007
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9. Mapa auto-organizÃvel com campo receptivo adaptativo local para segmentaÃÃo de imagens
A new self-organizing map with variable topology is introduced for image segmentation. The proposed network, called Local Adaptive Receptive Field Self-organizing Map (LARFSOM) is based on the Self-organizing Map (SOM) and Grow When Required (GWR). The model main features are: adaptive final number of nodes, variable topology, new node insertion based on sim
Publicado em: 2007
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10. Aplicação de análises estatística e neural para reconhecimento de sinais de odores
This work investigates the use of an electronic nose prototype for prognosis of Diabetes Mellitus. The work involves five main parts: (1) building of odors database by aroma sensors; (2) an evaluation of the odors database through multivariate statistics techniques;(3) use of Multilayer Perceptron (MLP) and Radial Basis Function (RBF) Artificial Neural Netwo
Publicado em: 2007
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11. ProposiÃÃo e avaliaÃÃo de algoritmos de filtragem adaptativa baseados na rede de kohonen / Proposition and evaluation of the adaptive filtering algorithms basad on the kohonen
A Rede Auto-OrganizÃvel de Kohonen (Self-Organizing Map - SOM), por empregar um algoritmo de aprendizado nÃo supervisionado, vem sendo tradicionalmente aplicada na Ãrea de processamento de sinais em tarefas de quantizaÃÃo vetorial, enquanto que redes MLP (Multi-layer Perceptron) e RBF (Radial Basis Function) dominam as aplicaÃÃes que exigem a aproxima
Publicado em: 2007
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12. Análise de métodos de agrupamento para o treinamento de redes neurais de base radical aplicadas à identificação de sistemas
For complex systems, modeling using basic laws to determine their dynamic behavior is not always possible. An alternative to solve these problems is use concepts of systems identification. Trough system identification it is possible to determine a mathematical model based on input and output data of the system. When little prior knowledge is available, it is
Publicado em: 2006