Several different methods have been used to sense load currents and extract its harmonic component in order to produce a reference current in shunt active power filters (SAPF), and to contribute significantly in determining the SAPF performance. Consequently, many structures based on artificial neural network (ANN) have been developed in the literature, The most significant have used at least two Adaline networks for introducing a controller which serves to keep the terminal capacitor voltage stable. This paper presents a novel method and design that utilises one Adaline network. The latter combines both the strategies for extracting the reference currents and controlling DC link voltage which ensure suitable transit of powers to supply the inverter. To investigate the performance of this identification method, the study has been accomplished using simulation with MATLAB Simulink Power System Toolbox. The simulation study results of this novel technique compared to other similar methods are found quite satisfactory by assuring good filtering characteristics and high system stability.
<span>In biometric systems, compression takes important place especially in order to reduce the size of the information stored or transmitted through the distributed biometric systems. It is also noted that the compression techniques induce loss of information in the compressed images that can affect the effectiveness of biometric systems. The main objective of our contribution is to examine the efficacy of the used method to offer an optimal compression quality in these kind of images without considerable distortion. In order to evaluate the efficacy of the compression process, we use two kinds of evaluation, full-reference image quality assessment and a new proposed textural quality analysis of the compressed images. In this paper, we use a second-generation wavelet transform to improve the compression study in biometric images. The basic idea of this algorithm is the quincunx wavelet transform coupled to a modified progressive encoder called SPIHT-Z encoding.</span>
Wavelet transforms and wavelet packets are widely imposed in the analysis and resolution of problems related to science and technical engineering. Decomposition wavelet packet allows several frequency bands according to various levels of resolutions. We apply this transform (PWT) coupled with the SPIHT coder to reduce the limitations of conventional wavelet filter bank. The results obtained using the applied algorithm, are very satisfactory and encouraging compared to many of the best coders cited in the literature and show a visual and numerical superiority over conventional methods. These the promising results are confirmed by visual evaluation parameters (PSNR, MSSIM and VIF).
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