A RBF network was used as an empirical modeling tool. Results on simulated processes show that such a network can learn the shape of the function reasonably well with very limited experimental data. The use of the RBF network model is also illustrated with real experimental data from a soil extraction process.

This paper presents a new sequential multi-category classifier using radial basis function (SMC-RBF) network for real-world classification problems. The classification algorithm processes the training data one by one and builds the RBF network starting with zero hidden neuron. The growth criterion uses the misclassification error, the approximation error to the true decision boundary and a dist...

Gaussian neural networks have always suffered from the curse of dimensionality; the number of weights needed increases exponentially with the number of inputs and outputs. Many methods have been proposed to solve this problem by optimally or sub-optimally selecting the weights or centers of the Gaussian neural network [1],[2]. However, most of these attempts are not suitable for online implemen...

The two well-known neural network, Hopfield networks and Radial Basis Function networks, have different structures and characteristics. Hopfield neural network and RBF neural network are two of the most commonly-used types of feedback networks and feedforward networks respectively. This study gives an overview for Hopfield neural network and RBF neural network in architectures, the learning pro...

We describe here the application of a type of artificial neural network, the Gaussian radial basis function (RBF) network, in the identification of a large number of phytoplankton strains from their 11-dimensional flow cytometric characteristics measured by the European Optical Plankton Analyser instrument. The effect of network parameters on optimization is examined. Optimized RBF networks rec...

In this paper we have studied adaptive equalization in the GSM (Global System for Mobile communications) environment using radial basis function (RBF) networks. Equalization is here considered as a classification problem, where the idea is to map the received complex-valued signal into desired binary values using RBF network equalizer. Results prove that the RBF network provides very good bit e...

Image Enhancement is for Improving Visibility and can also be used for different task, It is also important to provide a better representation for further automated image processing such as image analysis, detection, segmentation, recognition and data hiding which can be gain by image enhancement technique there are various method are available for the enhancement like histogram equalization et...

Personal credit evaluation is the basic method for the commercial banks to avoid the consumer credit risk. On one hand, the credit behavior of individuals is complex; on the other hand the personal credit assessment system in our country is not sound, assessment methods are mostly objective, therefore, more and better scientific methods for credit risk assessment need to be introduced. This pap...