radial basis function network identification
Dynamic Threshold Selection for Sequential Learning in Radial Basis Function Networks
... system identification have evolved over the years to provide better and faster learning capabilities with increasing automation of ...case basis will be proven, depending heavily on several of the system’s ...
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Writer Identification and Recognition Using Radial Basis Function
... Combining all the features given above, a feature vector of length 76 is constructed and given as input to each neural network. The input to neural network should be in the range of (-1, 1). So the features ...
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Learning enhancement of radial basis function network with particle swarm optimization
... So we can take a two-step training strategies to train them respectively. The First step is called unsupervised learning used to determine the center and widths of the RBF (structure identification stage) by ...
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Face Recognition by Radial Basis Function Network (RBFN)
... In the field of image processing, pattern recognition, computer vision, and neural network, every researcher concentrates on human face recognition by machine from still and video images. For doing this task, ...
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Orthonormal Basis and Radial Basis Functions in Modeling and Identification of Nonlinear Block-Oriented Systems
... a radial basis function network (RBFN) has been used to model a nonlinear static part of the Hammerstein and feedback-nonlinear systems and a very good identification performance has ...
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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 ...neural network (GRNN), radial ...
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Design of Hanman Entropy Network from Radial Basis Function Network
... tea-category identification (TCI) system is developed in [17] and it uses a combination of JAYA algorithm and fractional Fourier entropy on three images captured by a CCD ...
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Radial basis function neural network learning with modified backpropagation algorithm
... In addition, to train RBFNN, we can take a two-step training strategies. The first step is called unsupervised learning. Unsupervised learning is used to determine RBFNN centres and widths of the clusters with clustering ...
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The Face Recognition System By Using The Radial Basis Function Neural Network (RBFNN)
... At present, demand on the face recognition system is increasing with the needs of utilisation the system to keep the discretion, privacy and security to users. The common application can be seen in the digital chip in ...
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Radial Basis Function (RBF) Neural Network for Load Forecasting during Holiday
... neural network for short term load ...neural network model motivated by locally-tuned response biological neurons that provide selective response characteristics for some finite range of the input signal ...
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Research on Intention Recognition Method Based on Radial Basis Function Neural Network
... (radial basis function neural network model) was adopted in this paper to recognize the collaborator’s intention during human-robot ...neural network, the human-robot collaboration ...
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Symmetric Radial Basis Function Network Equaliser
... The paper investigates nonlinear equalisation using a novel symmetric radial basis function (RBF) network. By explicitly exploiting the inherently symmetric struc- ture of the optimal Bayesian ...
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An Optimal Radial Basis Function (RBF) Neural Network for Hyper-surface Reconstruction
... neural network with one neuron for each distinct ...regularization network requires the calculation of linear synaptic weights, selection of isotropic spread () and computation of an optimum level of ...
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ELECTRICITY CONSUMPTION PREDICTION SYSTEM USING A RADIAL BASIS FUNCTION NEURAL NETWORK
... neural network which feeds back part of its ...neural network is very applicable to this problem when energy consumption shows high ...(BP) network for enhanc- ing the accuracy of daily and hourly ...
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Multilingual Speech Recognition Using Radial Basis Function (RBF) Neural Network
... Neural Network and the second stage is speech recognition and Language Recognition of Bengali, Chhattisgarhi, English and Hindi speech signal with the combination of Particle Swarm Optimization (PSO) technique and ...
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Learning enhancement of radial basis function neural network with harmony search algorithm
... This dataset is presented to the inputs at the beginning of the learning process to determine the correct outputs. As in Kattan et al. (2010) an output value that is close to the desired output could be achieved through ...
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Iterative Application of the aiNET Algorithm in the Construction of a Radial Basis Function Neural Network
... Immune NETwork (aiNet) and the CLONal ALGorithm selection (CLONALG), which are applied together in tasks such as learning machine, pattern recognition, compression and clustering [Silva, ...
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An Adaptive Controller using Radial Basis Function Neural Network with Reinforcement Learning
... neural network is used to approximate the parameters of PID ...value function between successive states in the state ...RBF network are system error, as well as the first and the second order ...
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Radial Basis Function Assisted Turbo Equalization
... number of hidden nodes of each sub-RBF network is given by . In their seminal papers, Chen et al. [10], [12], [13] introduced decision feedback into the RBF equalizer in order to reduce its computational ...
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Adaptive Radial Basis Function Detector for Beamforming
... The optimal Bayesian nonlinear detection solution has an inherent symmetry because the signal states corresponding to the different signal classes are distributed symmetrically. This symmetric property is difficult to ...
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