IDIAP An RBF Network that Learns Some Aspectsof Perceptual

Idiap an Rbf Network That Learns Some Aspects of Perceptual Organization

Adaptive Modulation of OFDM by using Radial Basis Function Neural Network

Adaptive communication is one of the methods used for high rate communication with efficient spectrum efficiency and with improved accuracy for future wireless communication systems. In this paper, we propose an adaptive modulated Orthogonal Frequency Division Multiplexing (OFDM) system based on Radial Basis Function (RBF) and then their performance (MSE) and classification accuracy is evaluate...

Automatic Face Recognition using Radial Basis Function Networks

It is well known that the task of automatic face recognition in dynamic environments is very hard. The key problem is that everyday influences, such as lighting, head pose and expression, can lead to greater variation between images of the same person than between images of different people. However, there must be some essential invariant set of features that allow us to recognise familiar face...

A New Recurrent Radial Basis Function Network

Cheung and Xu 2001 has presented a dual structural recurrent radial basis function (RBF) network by considering the different scales in net’s inputs and outputs. However, such a network implies that the underlying functional relationship between the net’s inputs and outputs is linear separable, which may not be true from a practical viewpoint. In this paper, we therefore propose a new recurrent...

Evaluating Seepage of Dam Body Using RBF and GFF Models of Artificial Neural Network

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...