In this paper, investigate the use of brain activity for person identification. A biometric system is a technological system that uses information about a person. Research on brain signals show that each individual has a unique brain wave pattern. Electroencephalography signals generated by mental tasks are acquired to extract the distinctive brain signature of an individual. Electroencephalogr...

In this paper, investigate the use of brain activity for person identification. A biometric system is a technological system that uses information about a person. Research on brain signals show that each individual has a unique brain wave pattern. Electroencephalography signals generated by mental tasks are acquired to extract the distinctive brain signature of an individual. Electroencephalogr...

in this paper, the temperature distribution in workpiece and microstructure of welded zone in friction stir welding of aluminum 1100 alloys and the effect of the tool rotational speed on these parameters have investigated experimentally. also feed forward back propagation neural network has been used to predict the temperature of the workpiece during the welding process by considering the proce...

In this paper we propose a method for solving some well-known classes of Lane-Emden type equations which are nonlinear ordinary differential equations on the semi-innite domain. The proposed approach is based on an Unsupervised Combined Articial Neural Networks (UCANN) method. Firstly, The trial solutions of the differential equations are written in the form of feed-forward neural networks cont...

This paper investigates an online gradient method with innerpenalty for a novel feed forward network it is called pi-sigma network. This network utilizes product cells as the output units to indirectly incorporate the capabilities of higherorder networks while using a fewer number of weights and processing units. Penalty term methods have been widely used to improve the generalization performan...

The removal of chromaticity in high precision astrometric measurements is a very important challenge because chromaticity can represent a relevant source of systematic error; we perform this task using a feed forward neural network and focus on the usefulness of a proper preprocessing applied to the network parameters. We use a few statistical moments properly selected with a careful preprocess...

many efforts have been made to model the the hot deformation (dynamic recrystallization) flow curves of different materials. phenomenological constitutive models, physical-based constitutive models and artificial neural network (ann) models are the main methods used for this purpose. however, there is no report on the modeling of warm deformation (dynamic spheroidization) flow curves of any kin...

Skin recognition is used in many applications ranging from algorithms for face detection, hand gesture analysis, and to objectionable image filtering. In this work a skin recognition system was developed and tested. While many skin segmentation algorithms relay on skin color, our work relies on both skin color and texture features (features derives from the GLCM) to give a better and more effic...

We show that neural network classifiers can be helpful to discriminate Higgs production from background at LHC in the Higgs mass range MH ∼ 200GeV. We employ a common feed-forward neural network trained by the backpropagation algorithm for off-line analysis and the neural chip Totem, trained by the Reactive Tabu Search algorithm, which could be used for on-line analysis.