This paper presents an approach to model the nonlinear dynamic behaviors of the Automatic Depth Control Electrohydraulic System (ADCES) of a certain mine-sweeping weapon using Radial Basis Function (RBF) neural networks. In order to obtain accurate RBF neural networks efficiently, a hybrid learning algorithm is proposed to train the neural networks, in which centers of neural networks are optim...

Hierarchical RBF networks consist of multiple RBF networks assembled in different level or cascade architecture. In this paper, an evolved hierarchical RBF network was employed to detect the breast cancel. For evolving a hierarchical RBF network model, Extended Compact Genetic Programming (ECGP), a tree-structure based evolutionary algorithm and the Differential Evolution (DE) are used to find ...

In this paper, two feed forward neural network models have been presented to predict the Silicon Modification Level (SiML) of W319 aluminum alloys using the Thermal Analysis (T.A) parameters as inputs. The developed neural networks are a Multilayer Perceptron (MLP) network and a Radial Basis Function (RBF) network. The neural network models were found to predict the SiML accurately (R=0.99). Th...

LIAO, YI. Neural Networks for Pattern Classification and Universal Approximation (Under the direction of Dr. Shu-Cherng Fang and Dr. Henry L. W. Nuttle). This dissertation studies neural networks for pattern classification and universal approximation. The objective is to develop a new neural network model for pattern classification, and relax the conditions for Radial-Basis Function networks to...

Abstract A simple yet effective architectural design of radial basis function neural networks (RBFNN) makes them amongst the most popular conventional networks. The current generation network is equipped with multiple kernels which provide significant performance benefits compared to previous using only a single kernel. In existing multi-kernel RBF algorithms, formed by convex combination base/...

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...

A new learning algorithm called extreme learning machine (ELM) has recently been proposed for single-hidden layer feedforward neural networks (SLFNs) with additive neurons to easily achieve good generalization performance at extremely fast learning speed. ELM randomly chooses the input weights and analytically determines the output weights of SLFNs. It is proved in theory that ELM can be extend...

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...