Browsing by Author "Youcef Brik"

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    Neighborhood Component Analysis and Support Vector Machines for Heart Disease Prediction
    (Université de M'sila, 2019) Mohamed Djerioui; Youcef Brik; Mohamed Ladjal; Bilal Attallah
    Nowadays, one of the main reasons for disability and mortality premature in the world is the heart disease, which make its prediction is a critical challenge in the area of healthcare systems. In this paper, we propose a heart disease prediction system based on Neighborhood Component Analysis (NCA) and Support Vector Machine (SVM). In fact, NCA is used for selecting the most relevant parameters to make a good decision. This can seriously reduce the time, materials, and labor to get the final decision while increasing the prediction performance. Besides, the binary SVM is used for predicting the selected parameters in order to identify the presence/absence of heart disease. The conducted experiments on real heart disease dataset show that the proposed system achieved 85.43% of prediction accuracy. This performance is 1.99%higher than the accuracy obtained with the whole parameters. Also, the proposed system outperforms the state-of-the-art heart disease prediction
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    Sampling Rate Optimization for Improving the Cascaded Integrator Comb Filter Characteristics
    (Université de M'sila, 2020) Raouf Amrane; Youcef Brik; Samir Zeghlache; Mohamed Ladjal; Djamel Chicouche
    The cascaded integrator comb (CIC) filters are characterized by coefficient less and reduced hardware requirement, which make them an economical finite impulse response (FIR) class in many signal processing applications. They consist of an integrator section working at the high sampling rate and a comb section working at the low sampling rate. However, they don’t have well defined frequency response. To remedy this problem, several structures have been proposed but the performance is still unsatisfactory. Thence, this paper deals with the improvement of the CIC filter characteristics by optimizing its sampling rate. This solution increases the performance characteristics of CIC filters by improving the stopband attenuation and ripple as well as the passband droop. Also, this paper presents a comparison of the proposed method with some other existing structures such as the conventional CIC, the sharpened CIC, and the modified sharpened CIC filters, which has proven the effectiveness of the proposed method.