Abstract—This paper investigates threshold based neural networks for periodic symmetric Boolean functions and some related operations. It is shown that any n-input variable perio...
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
We study the problem of visualizing large networks and develop es for effectively abstracting a network and reducing the size to a level that can be clearly viewed. Our size reduc...
Due to the increasing reliance of our society on the timely and reliable transfer of large quantities of information (suchas voice, data, and video)across high speed communication...
Stavros D. Nikolopoulos, Andreas Pitsillides, Davi...
Motion detection and estimation is a first step in the much larger framework of attending to visual motion based on Selective Tuning Model of Visual Attention [1]. In order to be ...