The Radial Basis Function (RBF) technique is an interpolation method that produces high-quality unstructured adaptive meshes. However, the RBF-based boundary problem necessitates solving a large dense linear system with cubic arithmetic complexity computationally expensive and prohibitive in terms of memory footprint. In this article, we accelerate computations 3D mesh deformation based on RBF ...

: The Artificial Neural Network (ANN) is an Intelligence technique that offer many benefits including the ability to process a vast amount of data, learn from experiences, and good generalization capability. It was invented based on concept imitation human brain built up nodes are like neurons. Radial Basis Function (RBF) one established types ANN. Considering advantages great performance RBF, ...

This paper shows the results of the analysis of a scheme for Sensor Failure, Detection, Identification and Accommodation (SFDIA) using experimental flight data of a research aircraft model. Conventional approaches to the problem are based on observers and Kalman Filters while more recent methods are based on neural approximators. The work described in this paper is based on the use of neural ne...

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...

The automatic depth control electrohydraulic system of a certain minesweeping tank is complex nonlinear system, and it is difficult for the linear model obtained by first principle method to represent the intrinsic nonlinear characteristics of such complex system. This paper proposes an approach to construct accurate model of the electrohydraulic system with RBF neural network trained by geneti...

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...

Speaker identification is the computing task to identify an unknown identity based on the voice. A good speaker identification system must have a high accuracy rate to avoid invalid identity. Despite of last few decades’ efforts, accuracy rate in speaker identification is still low. In this paper, we propose a hybrid approach of unsupervised and supervised learning i.e. subtractive clustering a...

An integrated modeling and robust model predictive control (MPC) approach is proposed for a class of nonlinear systems with unknown steady state. First, the nonlinear system is identified off-line by RBF-ARX model possessing linear ARX model structure and state-dependent Gaussian RBF neural network type coefficients. On the basis of the RBF-ARX model, a combination of a local linearization mode...