nonlinear radial basis function neural network
Dynamic Threshold Selection for Sequential Learning in Radial Basis Function Networks
... for nonlinear system identification have evolved over the years to provide better and faster learning capabilities with increasing automation of ...the network. Automation as such allows neural ...
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Radial Basis Function Neural Network Trained by Adaptive Chaotic Particle Swarm Optimization to Control Nonlinear Systems
... In this paper, the CPSO technique is directly applied for optimizing all the modifiable parameters of a RBFNN to act as a feedback controller for nonlinear dynamical systems. Since the CPSO is a derivative-free ...
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Prediction of Salinity Variations in a Tidal Estuary Using Artificial Neural Network and Three Dimensional Hydrodynamic Models
... artificial neural network (ANN) technique using a back-propagation neural network (BPNN) and a radial basis function neural net- work (RBFNN) is adopted as an ...
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Adaptive Inverse Control of Proton Exchange Membrane Fuel Cell Using RBF Neural Network
... Proton exchange membrane fuel cells (PEMFCs) present remarkable control demands, due to the inherent nonlinear characteristics and time-varying parameters. This paper deals with the application of adaptive inverse ...
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Nonlinear Image Restoration Using a Radial Basis Function Network
... artificial neural net- works, called the radial basis function network (RBFN), has received considerable attention ...smooth function that achieves a good tradeo ff be- tween ...
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Medium term load demand forecast of Kano zone using neural network algorithms
... Neural network has gained wide acceptability over the last few decades, especially in the field of system identification, modelling and control applications ...complex nonlinear system and capable to ...
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Radial basis function neural network for software engineering measures A survey
... of radial basis Function network forms with the three layers, those are input layer, hidden layer and output ...the network. Next, hidden layer is formed with the Gaussian ...
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ELECTRICITY CONSUMPTION PREDICTION SYSTEM USING A RADIAL BASIS FUNCTION NEURAL NETWORK
... demand function for 17 groups of industries in Iran, using a Log- Linear Autoregression model with annual time-series data from 1980 to ...strongly nonlinear and ...
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Active Disturbance Rejection Control for a Class of Non affine Nonlinear Systems via Neural Networks
... on radial basis function (RBF) neural network is proposed for a class of non-affine nonlinear systems in this ...RBF neural network is used to approximate the ...
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Learning Methods of Radial Basis Function Neural Network
... forward neural network. Compared with BP network, RBF network not only has a physiological basis, but also the structure is simpler, the learning speed is ...theoretical basis, a ...
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Radial basis function neural network learning with modified backpropagation algorithm
... layers. Radial function is applied as activation function for all the neurons of the hidden ...and nonlinear transformation while on the other hand at the second stage, supervised learning is ...
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Learning enhancement of radial basis function neural network with harmony search algorithm
... Artificial neural network’s mimicking ability to human talent and their similarity to the structure of the neurons of the human brains attracted the eyes of many researchers due to its unparalleled properties, ...
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Iterative Application of the aiNET Algorithm in the Construction of a Radial Basis Function Neural Network
... Artificial Neural Networks (ANN); Expert Systems (ES) were used as a justification mechanism to ANN answers; Fuzzy Sets were used in the treatment of uncertain reasoning in ...
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The Face Recognition System By Using The Radial Basis Function Neural Network (RBFNN)
... the radial basis function network is an artificial neural network that uses radial basis functions as activation ...artificial neural network (ANN) is ...
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OPTIMIZATION OF HIGH VOLTAGE POWER SUPPLY FOR INDUSTRIAL MICROWAVE GENERATORS FOR ONE MAGNETRON
... Based on the proposed PSO with LIDWF and the chaotic local search, a two-phased iterative strategy named Chaotic PSO (CPSO) is proposed, in which PSO with LIDWF is applied to perform global exploration and CLS is ...
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Radial Basis Function Neural Networks : A Review
... a radial basis function neural network (RBFNN) to accurately recognize and predict the onset of Parkinson’s disease tremors in human ...new radial basis function ...
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A Radial Basis Function Approach to Retrieve Soil Moisture and Crop Variables from X-Band Scatterometer Observations
... newrb function. The neurons are added one by one to the network until the sum squared error falls beneath an error goal or a maximum number of neurons are ...regression neural network (GRNN) ...
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A Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems
... of nonlinear complementarity problem (NCP) functions is one of the motivations of our research ...Mittag-Leffler function and artificial neural networks that so far has not been utilized for the ...
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An Adaptive Controller using Radial Basis Function Neural Network with Reinforcement Learning
... The shortcoming of this technique is said to be its long execution time. This can be solved by reducing the number of the particles that hardly shows any effect in the given results and speeds up the algorithm. In this ...
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Designing and implementing a system for Automatic recognition of Persian letters by Lip-reading using image processing methods
... Bayesian network models," describes a speech processing system for Polish language, which uses both audio and video features, and is based on dynamic Bayesian network ...
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