Comparison between Wavelet and Radial Basis Function Neural Networks for GPS Prediction [PDF]
Engineering and Technology Journal, 2015 Neural networks are complex nonlinear models;this characteristic enables them to be used in nonlinear system modeling and prediction applications.The estimation and prediction are importantroles in the communication system.The proposed approach based ...
Farag Mahel Mohammed +2 more
doaj +1 more source
Computation of transient viscous flows using indirect radial basis function networks [PDF]
, 2007 In this paper, an indirect/integrated radial-basis-function network (IRBFN) method is further developed to solve transient partial differential equations (PDEs) governing fluid flow problems.
Mai-Cao, Lan +2 more
core +1 more source
Decision Feedback Equalizers Using Radial Basis Function Networks
Journal of King Saud University: Engineering Sciences, 2000 Decision feedback equalizers (DFE)s are used extensively in practical communication systems. They are more powerful than linear equalizers especially for severe inter-symbol interference (ISI) channels with deep frequency null.
S.A. Zummo, A. Balghonaim, M. Mohandes
doaj +1 more source
A new neural network technique for the design of multilayered microwave shielded bandpass filters [PDF]
, 2009 In this work, we propose a novel technique based on neural networks, for the design of microwave filters in shielded printed technology. The technique uses radial basis function neural networks to represent the non linear relations between the quality ...
Cañete Rebenaque, David +4 more
core +2 more sources
Solving high-order partial differential equations with indirect radial basis function networks [PDF]
, 2005 This paper reports a new numerical method based on radial basis function networks (RBFNs) for solving high-order partial differential equations (PDEs).
Mai-Duy, N., Tanner, R. I.
core +1 more source
Adaptive PID Controller for Active Suspension Using Radial Basis Function Neural Networks
Actuators, 2023 Suspension systems are critical parts of modern cars. In this study, a radial basis function neural networks-based adaptive PID optimal method is presented for vehicle suspension systems.
Weipeng Zhao, Liang Gu
doaj +1 more source
Random vibration analysis with radial basis function neural networks
International Journal of Dynamics and Control, 2021 Random vibrations occur in many engineering systems including buildings subject to earthquake excitation, vehicles traveling on a rough road and off-shore platform in random waves.
Xi Wang +3 more
semanticscholar +1 more source
Radial basis function networks with partially classified data [PDF]
, 1999 The problem of estimating a classification rule with partially classified observations, which often occurs in biological and ecological modelling, and which is of major interest in pattern recognition, is discussed.
MORLINI, Isabella
core +1 more source
Neural Networks For Electrohydrodynamic Effect Modelling [PDF]
Computer Science, 2004 This paper presents currently achieved results concerning methods of electrohydrodynamiceffect used in geophysics simulated with feedforward networks trained with backpropagation algorithm, radial basis function networks and generalized regression ...
Wiesław Wajs, Jolanta Gancarz
doaj +2 more sources
Radial basis function neural networks: a topical state-of-the-art survey
Open Computer Science, 2016 Radial basis function networks (RBFNs) have gained widespread appeal amongst researchers and have shown good performance in a variety of application domains. They have potential for hybridization and demonstrate some interesting emergent behaviors.
Dash Ch. Sanjeev Kumar +3 more
doaj +1 more source