ARTMAP neural network cla.c=;sifiers arc considered for the identification of radar emitter types from their waveform parameters. These classifiers can represent radar emitter type classes \vith one or more prototypes, perform on-line incremental learning to account for novelty encountered in the field, and process radar pulse streams at high speed, making them attractive for real-time applicat...

This paper investigates the application of a radial basis function (RBF) neural network to the prediction of field strength based on topographical and morphographical data. The RBF neural network is a two-layer localized receptive field network whose output nodes from a combination of radial activation functions computed by the hidden layer nodes. Appropriate centers and connection weights in t...

Hierarchical neural networks consist of multiple neural networks assembled in the form of an acyclic graph. The purpose of this study is to identify the hierarchical radial basis function neural networks and select important input features for each sub-RBF neural network automatically. Based on the pre-defined instruction/operator sets, a hierarchical RBF neural network can be created and evolv...

Dams have been always considered as the important infrastructures and their critical values are counted. Hence, evaluation and avoidance of dams’ destruction have a specific importance. Seepage occurrence in dams is an inevitable phenomenon. Despite all the progress in geotechnical engineering, up to now, seepage problem is the main conflict which occurs in dams. This study tried to estimate se...

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...

This paper studies the synchronization of SA and AV Node Oscillators using PSO optimized RBF-based controllers systems. High levels of control activities may excite unmodeled dynamics of a system. This matter changes the rules of controlling the system and achieving an acceptable control performance. In fact, the objective here is to reach a trade-off between tracking performance and parametric...

An accurate forecasting method for power generation of the wind energy conversion system (WECS) is urgently needed under the relevant issues associated with the high penetration of wind power in the electricity system. This paper proposes a hybrid method that combines orthogonal least squares (OLS) algorithm and genetic algorithm (GA) to construct the radial basis function (RBF) neural network ...

Among the many methods proposed in the literature for face recognition, those relying on the so called eigenfaces have been explored with great interest in the last few years. In those methods the face images are initially subjected to a PCA stage (Principal Component Analysis) for dimensionality reduction and then applied to a classifier. This work evaluates and compares two eigenface based fa...

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, the theory and construction methods of four models are presented for predicting the vegetable market price, which are BP neural network model, the neural network model based on genetic algorithm, RBF neural network model and an integrated prediction model based on the three models above. The four models are used to predict the Lentinus edodes price for Beijing Xinfadi wholesale m...