This paper presents the problem of multiple quadrature amplitude modulated signals equalization and argues the use of a radial basis functions neural network (RBF-NN) equalizer. Different competitive learning algorithms for the RBF-NN centres determination are discussed. A new competitive learning algorithm is introduced, the rival penalized competitive learning, which rewards the winner and pe...

In this paper a nonparametric neural network (NN) technique for prediction of future values of a signal based on its past history is presented. This approach bypasses modeling, identification, and parameter estimation phases that are required by conventional parametric techniques. A multi-layer feed forward NN is employed. It develops an internal model of the signal through a training operation...

Combining the ant colony algorithm (ACA) and the neural network (NN), the present paper puts forward an approach to traffic volume forecasting based on the ant colony neural network. The approach employs the ACA with mutation features to train the weights of an artificial neural network (ANN), thus it is characterized by large mapping capacity of the NN, and by rapidity, global convergence, and...

-As reported in [1], the Material Characteristics in Frequency Domain coupled with a 2 layer feed-forward Neural Network, MCFD/NN, has been successfully applied to soil moisture determination. The results were obtained under controlled laboratory conditions. Extension to open field soil moisture determination has been reported in [2] and it was shown that the MCFD/NN approach gives accurate res...

Purpose: discuss the role of the neural network (NN) theory in the computer network security evaluation. Method: propose three-level and four-class indicator system suitable for network security evaluation, establish the network security evaluation system model based on NN, optimize the NN model by using the particle swarm, collect 100group data on the computer network security evaluation of di...

This paper encompasses application of the Neural Network Tool (NN Tool) in the glass classification problem and also discusses the correlation of the different activation functions with the Mean Square Error (MSE). This paper works on the glass data classification and finds the impact of different Activation functions on the error obtained while training and testing of the neural network model ...

In this study, the altitude and yaw angle tracking is considered for a scale model helicopter, mounted on an experimental platform, in the presence of model uncertainties, which may be caused by unmodelled dynamics, or aerodynamical disturbances from the environment. To deal with the uncertainties, approximation-based techniques using neural network (NN) are proposed. In particular, two differe...

It is well known that computed torque robot control is subjected to performance degradation due to uncertainties in robot model, and application of neural network(NN) compensation techniques are promising. In this paper we examine the eeectiveness of neural network(NN) as a compensator for the complex problem of Cartesian space control. In particular we examine the diierences in system performa...

When the future information for an optimization model is not complete, the model tends to incorporate such uncertainties as some assumptions on the coefficients. As time passes and more precise information is accumulated, the initial optimal solution may no longer be optimal, or even feasible. At this point, model builders want to modify the assumed and controllable coefficients to obtain the d...

A neural network (NN) based adaptive output feedback controller is proposed for a class of nonlinear systems. In this control scheme, the adaptive output feedback NN controller is proposed by using an observer to estimate the states of the system. The weights of the neural network can be adjusted in terms of Lyapnuov’s stability criterion. The proposed controller can be applied to nonlinear sys...