ALI Khalfa

NECHE, SABRINE; , LAGGOUNE, CHAIMA

Débruitage du signal ECG basé par méthodes ondelettes Analyse composant principal (ACP)

Saghiour, Soulaf , LAmrai, Ahlam

SEPARATION AVEUGLE DE SOURCES (SAS) PAR OPTIMISATION HEPSO (HIGH EXPLORATION PARTICULE SWARM OPTIMISATION) : APPLICATION AUX SIGNAUX IMAGES

Benkhaled, Nour el houda; , Belgeuleil, Aicha

Séparation aveugle de sources (SAS) par optimisation BCO (Bee colony Optimization) dans mélange non-linéaire : Application aux signaux paroles

BALAH, Oualid

Séparation Aveugle de Signaux Audio Utilisant Particle Swarm Optimisation (PSO)

Kadiri, Wahiba; , Khenache, Bouchra

Séparation Aveugle de Signaux Audio en Utilisant les Statistique D'ordre Supérieur

ZERGUI, MALIKA

Separation aveugle de source de melange instantane pour signaux paroles

In this correspondence, two exact closed-form expressions for the probability of false alarm have been derived assuming a homogeneous Gamma distributed clutter. These expressions concern both the cell averaging CFAR (CA-CFAR) and the greatest of CFAR (GO-CFAR) detectors. As it will be shown, the proposed expressions are given in terms of the Gauss hypergeometric function and the second Appell function. Our expressions are then examined and validated numerically, by comparing them to their counterparts computed using numerical integrals and Monte-Carlo simulations, considering various scenarios.

Citation

ELhadi KENANE , Mohamed SAHED , Ali KHALFA , Farid Djahli, , (2023), Exact Closed-Form Pfa Expressions for CA- and GO-CFAR Detectors in Gamma-Distributed Radar Clutter, IEEE Transactions on Aerospace and Electronic Systems, Vol:59, Issue:4, pages:4674 - 4679, IEEE

This letter presents an analytical study of the performance of the maximum-likelihood gamma constant false alarm rate (MLG-CFAR) detector operating over a homogenous gamma-distributed (GM) clutter. To accomplish this task, a novel closed-form expression for the probability of false alarm and a highly accurate approximation for the probability of detection are derived. Specifically, this proposed approximation is also given in a closed form. These expressions, which can be of great interest to the radar community, are given in terms of the Gauss hypergeometric function and the Tricomi function. Besides, the proposed expressions can be easily implemented and computed using most popular scientific software packages such as MATLAB, Maple, and Mathematica. Our propositions are then tested and validated using numerical computing and Monte Carlo simulations. The obtained results demonstrate a high accuracy and significant computational advantages of the proposed expressions compared to the alternative ones. Moreover, the detection performance of the MLG-CFAR detector is also conducted assuming a homogenous clutter with a known shape parameter.

Citation

Mohamed SAHED , ELhadi KENANE , Ali KHALFA , fdjahli@yahoo.fr, , (2023), Performance Analysis of the MLG-CFAR Detector in Homogenous Gamma-Distributed Sea Clutter, IEEE Geoscience and Remote Sensing Letters, Vol:20, Issue:2023, pages:1-5, IEEE

Signal and image separation are extensively used in numerous imaging applications and communication systems. In this paper, a novel Blind Source Separation (BSS) approach, based on the Hybrid Firefly Particle Swarm Optimization (HFPSO), is proposed for separating mixed images. This approach processes the observed source without any prior knowledge about the model and the statistics of the source signal. The proposed method presents high robustness against local minima and converges quickly to the global minimum. Via numerical simulations, the proposed approach is tested and validated in comparison with standard Particle Swarm Optimization (PSO), Robust Independent Component Analysis (RobustICA), and Artificial Bee Colony (ABC) algorithms. The obtained results show that the presented technique outperforms the existing ones in terms of quality of image separation, the Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Measure (SSIM). Moreover, the obtained results demonstrate that our approach provides also promising results in image separation from noisy mixtures.

Citation

ELhadi KENANE , Ali KHALFA , Mohamed SAHED , Farid Djahli, , (2022), A Novel Blind Image Source Separation Using Hybrid Firefly Particle Swarm Optimization Algorithm, Engineering, Technology & Applied Science Research, Vol:12, Issue:6, pages:9680-9686, ETASR

Blind source separation (BSS) concerns the signal processing techniques that aim to find several elementary components of sources from linear combinations of these sources received on several sensors. This paper presents a method for the extraction of these independent components. It is called Joint Approximate Diagonalization of Eigenmatrices (JADE) and uses fourth-order cumulants. A simulation example shows the performance of the proposed algorithm by displaying its high separation accuracy. The proposed technique is compared to the Equivariant Adaptive Source Separation Algorithm (EASI).

Citation

ELhadi KENANE , Ali KHALFA , Amardjia Noureddine, , (2022), Blind Image Separation Using the JADE Method, engproc, Vol:14, Issue:1, pages:1-7, MDPI Tongzhou Office, Beijing

Blind source separation (BSS) concerns the signal processing techniques that aim to find several elementary components of sources from linear combinations of these sources received on several sensors. This paper presents a method for the extraction of these independent components. It is called Joint Approximate Diagonalization of Eigenmatrices (JADE) and uses fourth-order cumulants. A simulation example shows the performance of the proposed algorithm by displaying its high separation accuracy. The proposed technique is compared to the Equivariant Adaptive Source Separation Algorithm (EASI)

Citation

ELhadi KENANE , Ali KHALFA , Amardjia Noureddine, ,(2021), Blind Image Separation Using Joint Approximate Diagonalization of Eigenmatrices (JADE) Method,ICCEIS2021,University of Boumerdes

Blind Source Separation (BSS) is a technique used to separate supposed independent sources of signals from a given set of observations. In this paper, the High Exploration Particle Swarm Optimization (HEPSO) algorithm, which is an enhancement of the Particle Swarm Optimization (PSO) algorithm, has been used to separate a set of source signals. Compared to PSO algorithm, HEPSO algorithm depends on two additional operators. The first operator is based on the multi-crossover mechanism of the genetic algorithm while the second one relies on the bee colony mechanism. Both operators have been employed to update the velocity and the position of the particles respectively. Thus, they are used to find the optimal separating matrix. The proposed method enhances the overall efficiency of the standard PSO in terms of good exploration and performance. Based on many tests realized on speech and music signals supplied by the BSS demo, experimental results confirm the robustness and the accuracy of the introduced BSS technique.

Citation

Ali KHALFA , ELhadi KENANE , Nourredine AMARDJIA, Djamel chikouche, Abdelouahab Attia, , (2019), Blind Audio Source Separation Based On High Exploration Particle Swarm Optimization, KSII Transactions on Internet and Information Systems, Vol:13, Issue:5, pages:2574-2587, TIIS

The radar analyst can develop and use mathematical and statistical techniques that lead to accurate prediction or adapting models for estimating the target detection performance. In radar detection theory, detection probability, false alarm probability, number of samples non-coherently integrated for a detection test, and signal-to-noise ratio (SNR) are closely interrelated. The present paper is intended to provide an overview of the calculations of radar probability of detection and its related parameters. The main methods and procedures for predicting the detection performance of either non-fluctuating or fluctuating targets are described. Performance’s analysis of the studied models is included, along with some graphical simulation examples.

Citation

Ali KHALFA , , (2017-04-01), Analysis Study of Radar Probability of Detection for Fluctuating and Non-fluctuating Targets, Algerian Journal of Signals and Systems, Vol:2, Issue:1, pages:12-20, LSS

This paper presents a solution to enhance the Global Navigation Satellite System (GNSS) positioning by mitigating the multipath (MP) influence. In several cases GNSS navigation such as Global Positioning System (GPS) and Future Galileo needs a very high accuracy in positioning. As MP is a major source of inaccuracy, we propose to use the concept of Binary-Asymmetric Phase-Only Correlation (BA–POC) in the GNSS receivers in order to estimate LOS delay of received signal. BAPOC was applied to the area of ranging to help identifying the line of sight (LOS) in MP-abundant environments, Using the aforementioned scheme, the MP induced bias can be efficiently reduced. The obtained results show that the proposed scheme gives better performance over existing correlation-based schemes. Thus, it results in a high accuracy in GNSS positioning.

Citation

Ali KHALFA , ,(2016-10-24), Analysis Study of Radar Probability of Detection for Fluctuating and Non-fluctuating Targets,International Conference on Technological Advances in Electrical Engineering Skikda, Algeria, 24-26 October 2016,Skikda, Algeria,

This paper presents a solution to enhance the Global Navigation Satellite System (GNSS) positioning by mitigating the multipath (MP) influence. In several cases GNSS navigation such as Global Positioning System (GPS) and Future Galileo needs a very high accuracy in positioning. As MP is a major source of inaccuracy, we propose to use the concept of Binary-Asymmetric Phase-Only Correlation (BA–POC) in the GNSS receivers in order to estimate LOS delay of received signal. BAPOC was applied to the area of ranging to help identifying the line of sight (LOS) in MP-abundant environments, Using the aforementioned scheme, the MP induced bias can be efficiently reduced. The obtained results show that the proposed scheme gives better performance over existing correlation-based schemes. Thus, it results in a high accuracy in GNSS positioning.

Citation

Ali KHALFA , ,(2009-03-22), Application of the BA-POC scheme for multipath mitigation in GPS/Galileo receivers,5 th International Conference: Sciences of Electronic, Technologies of Information and Telecommunications March 22-26, 2009 – Tunisia,Tunisia