This paper is concerned with the consensus tracking problem of high order MIMO nonlinear multi-agent systems. The agents must follow a leader node in presence of unknown dynamics and uncertain external disturbances. The communication network topology of agents is assumed to be a fixed undirected graph. A distributed adaptive control method is proposed to solve the consensus problem utilizing re...

This paper presented the Minimal Radial Basis Function Network (MRBFN) approach busbar protection. The Optical Current Transducer (OCT) is used to solve the magnetic saturation so as to improve the reliability of the system. Performance of this model is compared with Feed Forward Back Propagation Neural Network (FFBP). The proposed model is more accurate in prediction with few numbers of hidden...

The judgment of forged passports plays an important role in the immigration control system and requires the automatic recognition of passports as the pre-phase processing. This paper, for the recognition of passports, proposed a novel method using the enhanced RBF network based on ART2. The proposed method extracts code sequence blocks and individual codes by applying the Sobel masking, the sme...

In this study, the performance of two neural classifiers; namely Multi Layer Perceptron (MLP) and Radial Basis Fuction (RBF), are compared for a multivariate classification problem. MLP and RBF are two of the most widely neural network architecture in literature for classification and have successfully been employed for a variety of applications. A nonlinear scaling scheme for multivariate data...

Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this problem uses time series forecasting by neural networks. However, time series forecasting is a difficult problem, thus, the use of this technique for time series novelty detection is sometimes criticized. Alternativel...

In this paper the popular PD controller of robot manipulator is modified. RBF neural networks are used to compensate the gravity and fi-iction. No exact knowledge of the robot dynamics is required. The euggeated learning law of neuro compensator is similar to the well-known backpropagation algorithm but wit h addit ional robust terms. Lyapuuov-liie analysis is used to derive the stability of le...

The spatial interpolation comparison 97 is concerned with predicting the daily rainfall at 367 locations based on the daily rainfall at nearby 100 locations in Switzerland. We propose a divide -and-conquer approach where the whole region is divided into four sub-areas and each is modeled with a different method. Predictions in two larger areas were made by RBF networks based on the locational i...

We propose a test for ARCH that uses a radial basis function artificial neural network. It outperforms alternative neural network tests in a variety of Monte Carlo experiments.  2000 Elsevier Science S.A. All rights reserved.

Face is an important biometric feature for personal identification. This paper describes a new face verification methods based on singular value decomposition and RBF neural networks. The proposed method utilizes the positive samples and negative samples learning ability of RBF neural networks to improve singular values based face verification. Experiment results show that the novel face verifi...

In this paper, a novel self-creating disk-cell-splitting (SCDCS) algorithm is proposed for training the radial wavelet neural network (RWNN) model. Combining with the least square (LS) method which determines the linear weight coefficients, SCDCS can create neurons adaptively on a disk according to the distribution of input data and learning goals. As a result, a disk map is made for input data...