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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

“…Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
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On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems by Mohammed Ahmed, Adeeb Ali

“…The optimal antenna could be chosen based on the transmitted power by selecting the preceding channel estimation. …”
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Grouping based radio frequency identification anti-collision protocols for dense internet of things application by Umelo, Nnamdi H., Noordin, Nor K., A. Rasid, Mohd Fadlee, Geok, Tan K., Hashim, Fazirulhisyam

“…This paper analyzes selected grouping-based algorithms. Their underlining principles are discussed including their tag estimation methods. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

“…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

“…The selection is based on the user preferences since it uses a self-learning algorithm to determine triggers and handover thresholds dynamically. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

“…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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Evaluating A New Adaptive Group Lasso Imputation Technique For Handling Missing Values In Compositional Data by Tian, Ying

“…Considering the impact of outliers on the accuracy of estimation, both simulation and case analysis are conducted to compare the proposed algorithm against four existing methods. …”
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An efficient algorithm for oval shape face detection in color family photos by Hanafi, Marsyita, Wan Adnan, Wan Azizun, S. Ahmad, S. M.

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Artificial Robust Control of Robot Arm: Design a Novel SISO Backstepping Adaptive Lyapunov Based Variable Structure Control. by Sulaiman, Nasri, Piltan, Farzin, Jalali, Amin, Siamak, Sobhan, Nazari, Iman

“…The fuzzy backstepping methodology is on-line tune the variable structure function based on adaptive methodology. The performance of the SISO VSC which controller coefficient is on-line tuned by fuzzy backstepping algorithm (FBSAVSC) is validated through comparison with VSC and proposed method. …”
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Subspace Techniques for Brain Signal Enhancement by Kamel , Nidal, Yusoff, Mohd Zuki

“…Both the simulation and real human data show that the subspace methods generate reasonably low errors and high success rate. …”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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Comparisons of Signal Subspace Methods for Estimating Visual Evoked Potentials by Yusoff, Mohd Zuki, Nidal S., Kamel

“…Out of the two mentioned subspace, only the former is selected for further processing. Specifically, two eigendecomposition based signal subspace methods containing unique basis and estimator matrices were developed and their efficiency and performance were compared between each other. …”
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Facial age range estimation using geometric ratios and hessian-based filter wrinkle analysis by Razalli, Husniza

“…The Hessian-Based Filter is used to enhance wrinkle analysis for age range estimation method. …”
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New CFAR algorithm and circuit development for radar receiver by Kamal, Mustafa Subhi

“…Therefore, the MSS-CA-CFAR is chosen to implement by practical digital circuit and there is another important feature in the MSS-CFAR algorithm that is parallel processing since the spike selection process is done at the same time with summing of samples process that makes this algorithm much less in processing time from any other algorithm using the same environment. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

“…A new detection algorithm based on QR decomposition, denoted as LC-QR, is proposed. …”
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Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models by Abdul Muthalib, Maiyastri

“…In the beginning, the division of the data is based on the plot of the returns, but for the later part, it is based on the distribution of the returns. …”
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UV-vis spectrophotometric and artificial neural network for estimation of ammonia in aqueous environment using cobalt(ii) ions by Ling Ling T., Ahmad M., Yook Heng L.