Mohammed Mekideche

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In this article an attempt is made to study the applicability of a general purpose, supervised feed forward neural network with one hidden layer, namely radial basis function (RBF) neural network and finite element method (FEM) to solve the inverse problem of parameter identification. The methodology used in this study consists in the simulation of a large(More)
This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study(More)
In computer vision and image processing, the Canny edge detector algorithm is the most widely implemented from performance point of view. In this paper, attempting to reduce the computational time of this algorithm on skipping the smoothing step, a fractional integral mask (FIM) is introduced and investigated. It has been shown that the smoothing operation(More)
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