Neural Networks Applied to Welding. Two Examples.

Multiplicative cascades applied to PDEs (two numerical examples)

Numerical approximations to the Fourier transformed solution of partial differential equations are obtained via Monte Carlo simulation of certain random multiplicative cascades. Two particular equations are considered: linear diffusion equation and viscous Burgers equation. The algorithms proposed exploit the structure of the branching random walks in which the multiplicative cascades are defin...

Neural Networks applied to wireless communications

A b s t r a c t . This paper presents a time-delayed neural network (TDNN) model that has the capability of learning and predicting the dynamic behavior of nonlinear elements that compose a wireless communication system. This model could help speeding up system deployment by reducing modeling time. This paper presents results of effective application of the TDNN model to an amplifier, part of a...

Neural Networks Applied to Smart Structure Control

LVQ Neural Networks Applied To Face Segmentation

Color-segmentation is quite sensitive to changes in light intensity. Many algorithms do not tolerate variations in color hue which correspond, in fact, to the same object. In this work an image segmentator algorithm based on Learning Vector Quantization (LVQ) networks is proposed and tested on a tracking application. In LVQ networks, neighboring neurons learn to recognize neighboring sections o...

Neural Networks Applied to Optimal Flight Control

This paper presents a method for developing control laws for nonlinear systems based on an optimal control formulation. Due to the nonlinearities of the system, no analytical solution exists. The method proposed here uses the 'black box' structure of a neural network to model a feedback control law. The network is trained with the back-propagation learning method by using examples of optimal co...