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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Bahaa Al-Sheikh
American University of the Middle East
Computer Science & IT Electrical & Electronics Engineering

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Application of optimization algorithms for classification problem Alaa Eleyan; Mohammad Shukri Salman; Bahaa Al-Sheikh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp4373-4379

Abstract

The work presented in this paper investigates the use of metaheuristic optimization algorithms for the face recognition problem. In the first setup, a face recognition system is implemented using particle swarm optimization (PSO) and firefly optimization algorithms, separately. PSO and firefly are used for forming the feature vectors in the feature selection stage. These feature vectors serve as the new representation for the face images that will be fed to the classifier. In the second setup, selected features from both PSO and firefly algorithms are fused to form one single feature vector for each face image before the classification stage. Extensive simulations are conducted using Poznan University of Technology (PUT) and face recognition technology (FERET) face databases. Optimal values for population size and maximum iterations number were selected before conducting the experiments. The effect of using different numbers of selected features on the performance is investigated for feature selection using PSO, firefly, and feature fusion of both.
Discrete-wavelet-transform recursive inverse algorithm using second-order estimation of the autocorrelation matrix Mohammad Shukri Salman; Alaa Eleyan; Bahaa Al-Sheikh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 6: December 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i6.16191

Abstract

The recursive-least-squares (RLS) algorithm was introduced as an alternative to LMS algorithm with enhanced performance. Computational complexity and instability in updating the autocolleltion matrix are some of the drawbacks of the RLS algorithm that were among the reasons for the intrduction of the second-order recursive inverse (RI) adaptive algorithm. The 2nd order RI adaptive algorithm suffered from low convergence rate in certain scenarios that required a relatively small initial step-size. In this paper, we propose a newsecond-order RI algorithm that projects the input signal to a new domain namely discrete-wavelet-transform (DWT) as pre step before performing the algorithm. This transformation overcomes the low convergence rate of the second-order RI algorithm by reducing the self-correlation of the input signal in the mentioned scenatios. Expeirments are conducted using the noise cancellation setting. The performance of the proposed algorithm is compared to those of the RI, original second-order RI and RLS algorithms in different Gaussian and impulsive noise environments. Simulations demonstrate the superiority of the proposed algorithm in terms of convergence rate comparedto those algorithms.
Co-Authors Alaa Eleyan Alaa Eleyan Mohammad Shukri Salman