The system gender classification from face images based on textural analysis and an artificial neural network. Face granulation process is applied for input faces for slices representation using Difference of gaussian approach. Here Weber’s Local Descriptor is used for gender recognition. Here this local descriptor extends it by introducing local spatial information through divide an image into...

In this work, we investigate the real-time identification problem of dynamic non-linear systems using a neural network approach. The neural network model structure is chosen to be the Gaussian Radial Basis Function (RBF) type, due to its universal approximation property and also to the fact that the parameters are linearly related to the outputs, allowing linear learning algorithms, with fast c...

The present paper proposes a fault diagnosis methodology of three phase inverter circuit base on radial basis function (RBF) artificial neural network trained by particle swarm optimization (PSO) algorithm. Using the appropriate stimulus signal, fault features are extracted from efficient points in frequency response of the circuit directly and then a fault dictionary is created by collecting s...

| Adaptive methods for demodulating multiuser communication in a Direct-Sequence Spread-Spectrum Multiple-Access (DS/SSMA) environment are investigated. In this setting the noise is characterized as being the sum of the interfering users' signals and additive Gaussian noise. The optimal receiver for DS/SSMA systems has a complexity that is exponential in the number of users. Adaptive Radial Bas...

In this paper, has been presented a stable method for predicting the ECG signals through the RBF neural networks, by the PSO algorithm. In spite of quasi-periodic ECG signal from a healthy person, there are distortions in electrocardiographic data for a patient. Therefore, there is no precise mathematical model for prediction. Here, we have exploited neural networks that are capable of complica...

This paper proposes a new blind watermarking scheme based on discrete wavelet transform(DWT) domain. The method uses the HVS model, and radial basis function neural networks(RBF). RBF will be implemented while embedding and extracting watermark.The human visual system (HVS) model is used to determine the watermark insertion strength. The neural networks almost exactly recover the watermarking s...

Radial Basis Function Neural Networks (RBF NNs) are one of the most applicable NNs in the classification of real targets. Despite the use of recursive methods and gradient descent for training RBF NNs, classification improper accuracy, failing to local minimum and low-convergence speed are defects of this type of network. In order to overcome these defects, heuristic and meta-heuristic algorith...

Water temperature is considered to be the most important parameter which can largely determine the aquaculture production of sea cucumbers, so it is extremely important to monitor and forecast the water temperature at different water depths. As the change of water temperature is a complex process which can not be exactly described with a certain formula, the artificial neural network characteri...

Artificial neural network based equalizers can be used for equalization in coherent optical OFDM systems. The artificial neural network based multilayer layer perceptron is a feed-forward network consists of one hidden layer with one or more hidden nodes between its input and output layers and can be trained by using back propagation algorithm. However, this algorithm suffers from slow converge...

Based on radial basis function neural network (RBF NN),the paper proposed a new algorithm for strip shape recognition. Compared with back propagation (BP) algorithm and improved least squares method (LSM), RBF NN shows excellent overall performance, such as learning speed, recognition precision and anti-interference capability. Copyright©2005IFAC Keyword: Strip Shape, Pattern Recognition, RBF,B...