Every time computer user asked to keep secret their passwords for various purposes. But memorization of all the passwords always is a tedious job. In this paper, we construct a Hash Function based on Feed Forward Neural Network. Hash Function is one way and secure against Man-in-the-Middle attack. Wired Equivalent Privacy is a well known Wireless Protocol used by every wireless communication us...

Face recognition is one of the biometric methods that is used to identify any given face image using the main features of this face. In this research, a face recognition system was suggested based on four Artificial Neural Network (ANN) models separately: feed forward backpropagation neural network (FFBPNN), cascade forward backpropagation neural network (CFBPNN), function fitting neural networ...

In this paper the RSA algorithm has been implemented with feed forward artificial neural network using MATLAB. This implementation is focused on the network parameters like topology, training algoritahm, no. of hidden layers, no. of neurons in each layer and learning rate in order to get the more efficient results. Many examples are tested and it is obtained that two hidden layers feed forward ...

Facial expression recognition has attracted much attention in recent years because of its importance in realizing highly intelligent human-machine interfaces. In this paper, we propose a new facial expression recognition technique that utilizes the 2-D DCT of full size facial images and eigenvectors based feed forward neural network. The neural network is designated to separate group of facial ...

The optimum design of solar energy systems strongly depends on the accuracy of  solar radiation data. However, the availability of accurate solar radiation data is undermined by the high cost of measuring equipment or non-functional ones. This study developed a feed-forward backpropagation artificial neural network model for prediction of global solar radiation in Makurdi, Nigeria (7.7322  N lo...

infiltration rate is one of the most important soil physical parameters and is a basic input data in irrigation and drainage projects. although, a number of theoretical or experimental based equations are presented to describe this phenomenon but the evaluation of some new sciences such as artificial neural networks, for prediction of the phenomenon can be investigated. generally, the infiltrat...

Artificial neural networks are finding many uses in the medical diagnosis application. The goal of this paper is to evaluate artificial neural network in disease diagnosis. Two cases are studied. The first one is acute nephritis disease; data is the disease symptoms. The second is the heart disease; data is on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient class...

Since past few years, researchers have been concentrating on the classification of Electromyography Signal. This method is very useful in diagnosing the neuro-muscular disorders, which consists of wide spread diseases affecting peripheral nervous system. Progressive muscle weakness is the major form of these disorders. Out of various proposed methods, scholars are commonly focusing on Neural Ne...

Multivariable regression and artificial neural network procedures were used to modeling of the input power and gas holdup of flotation. The stepwise nonlinear equations have shown greater accuracy than linear ones where they can predict input power, and gas holdup with the correlation coefficients of 0.79 thereby 0.51 in the linear, and R2=0.88 versus 0.52 in the non linear, respectively. ...