The Electrocardiogram (ECG) plays significant role in assessing patients with abnormal activity in their heart. ECG recordings of the patient taken to analyze abnormality and classify type of disorder present in the heart functionality. An Electrocardiogram is a bioelectrical signal that records the heart’s electrical activity versus time. It is used to measure the rate and regularity of heartb...

Building on previous work in Chinese character recognition, we describe an advanced system of classification using probabilistic neural networks. Training of the classifier starts with the use of distortion modeled characters from four fonts. Statistical measures are taken on a set of features computed from the distorted character. Based on these measures, the space of feature vectors is transf...

Hand gestures are a natural and efficient means to control systems one of the promising but challenging areas human–machine interaction (HMI). We propose system recognize by processing interrupted patterns light in visible communications (VLC) system. Our solution is aimed at emerging communication can facilitate human–computer for services health-care, robot systems, commerce home. The exploit...

We propose a self–adaptive probabilistic neural network model, which incorporates optimization algorithms to determine its spread parameters. The performance of the proposed model is investigated on two protein localization problems, as well as on two medical diagnostic tasks. Experimental results are compared with that of feedforward neural networks and support vector machines. Different sampl...

Object recognition and classification is a common problem facing computers. There are many shortcomings in proper identification of an object when it comes to computer algorithms. A very common process used to deal with classification problems is neural networks. Neural networks are modelled after the human brain and the neuron firings that occur when an individual looks at an image and identif...

In this study, we evaluate the accuracy of classifiers for classification of ultrasonic liver tissues. Two different statistic classifiers ami three various artificial neural networks are included: Bayes classifier k-nearest neighbor classifier. Back-propagation neural networks, probabilistic neural network and modified probabilistic neural network. These Jive different classifiers were investi...