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In this letter, a new approach for the learning process of multilayer feedforward neural network is introduced. This approach minimizes a modified form of the criterion used in the standard backpropagation algorithm. This criterion is based on the sum of the linear and the nonlinear quadratic errors of the output neuron. The quadratic linear error signal is(More)
Tracking of the skin disease is a necessary step of diagnostic as well the measure of the wound's surface is very useful in healing's document. To overcome the difficulties of the skin illness's estimation, encountered with the currently used measurement techniques, we propose a novel approach aiming to reduce the time-consuming and the error rate. The(More)
A novel method of colour image segmentation based on fuzzy homogeneity and data fusion techniques is presented. The general idea of mass function estimation in the Dempster-Shafer evidence theory of the histogram is extended to the homogeneity domain. The fuzzy homogeneity vector is used to determine the fuzzy region in each primitive colour, whereas, the(More)
In this paper, the Davidon Fletcher Powell (DFP) algorithm for nonlinear least squares is proposed to train multilayer perceptron (MLP). Applied on both a single output layer perceptron and MLP, we find that this algorithm is faster than the Marquardt-Levenberg (ML) algorithm known as the fastest algorithm used to train MLP until now. The number of(More)
delay times are thereafter implemented in the FPGA so as to synthesize the suitable gate pulse patterns for the semiconductor-controlled devices. It is shown that the proposed implementation method enables high switching frequency operation with high pulse resolution as well as a negligible propagation time for the generation of the gating pulses.(More)