The aim of this work is to examine how Artificial Neural Nets (ANN) can be used as a computerized method for electromyographic diagnosis. For this reason, a number of well defined neuromuscular disorders have been selected, ...

Various neural learning procedures have been proposed by different researchers in order to adapt suitable controllable parameters of neural network architectures. These can be from simple Hebbian procedures to complicated ...

A large number of different neural network structures have been constructed, trained and tested to a large data base of pregnant women characteristics, aiming at generating a classifier-predictor for the presence of ...

Forcasting the minimum temperature(Tmin) is one of the most important operational practices carried out by Meteorological Services worldwide. The great interest in developing methods for more accurate predictions has led ...

A selection of artificial neural network models were built and implemented for systematically study the contribution and the sensitivity of the main influencing parameters as important contributing factors for the non-invasive ...

Two different systems are introduced, that perform automated audio annotation and segmentation of Cypriot folk songs into meaningful musical information. The first system consists of three artificial neural networks (ANNs) ...

Bispectral analysis suggests that EMG is highly non-Gaussian at force level (FL) = 10% of maximum voluntary contraction

A three-layer neural network (NN) with novel adaptive architecture has been developed. The hidden layer of the network consists of slabs of single neuron models, where neurons within a slab-but not between slabs- have the ...