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Simulation of fast recursive least square algorithm for echo cancellation system by Kamaruddin, Rosita

“…The performance of FRLS algorithm for both filters is described and evaluated by using MATLAB software .. …”
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Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

“…Method 1 is a modification of Sebert’s method where the list squares (LS) fit is replaced by the least median of squares (LMS) fit while Method 2 is a modification of Sebert’s method where the least squares (LS) fit is replaced by the least trimmed of squares (LTS) fit. …”
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Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach by Ab. Malik, Rosely, Jamil S., Mohamed

“…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

“…The results also show that the proposed method outperforms other LMS algorithm without secondary path modelling. …”
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Heartbeat Anomaly Detection Method Based on Electrocardiogram using Improved Certainty Cognitive Map by Sumiati, .

“…The test results of the MCM Method gave a Mean Squared Error (MSE) of 0.65 and Root Mean Squared Error (RMSE) of 0.80 and the test results of the CCM Method with a Mean Squared Error (MSE) of 0.15 and a Root Mean Squared Error (RMSE) of 0.39. …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Muhammad Hasbollah, Hassan, Lidyana, Roslan, Muhamad Sukri, Hadi

“…The obtained results were then compared with the conventional method that is recursive least square (RLS). …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Lidyana, Roslan, Muhammad Hasbollah, Hassan

“…The obtained results were then compared with the conventional method that is recursive least square (RLS). The developed models were evaluated based on the lowest mean square error (MSE), within the 95% confidence level of both auto and cross-correlation tests as well as high stability in the pole-zero diagram. …”
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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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Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm by Ahirwal, M.K., Kumar, A., Singh, G.K.

“…ANCs are also implemented with Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm. …”
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Development of an Image Encryption Algorithm using Latin Square Matrix and Logistics Map by Emmanuel Oluwatobi Asani, Godsfavour Biety-Nwanju, Abidemi Emmanuel Adeniyi, Salil Bharany, Ashraf Osman Ibrahim Elsayed, Anas W. Abulfaraj, Wamda Nagmeldin

“…The issue of misplaced pixel positions in the image was also adequately addressed, making it an effective method for image encryption. The hybrid technique was simulated on image data and evaluated to gauge its performance. …”
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Improved Switching-Basedmedian Filter For Impulse Noise Removal by Teoh, Sin Hoong

“…Based on the evaluations from root mean square error (RMSE), false positive detection rate, false negative detection rate, mean structure similarity index (MSSIM), processing time, and visual inspection, it is shown that the proposed method is the best method when compared with seven other state-of-the art median filtering methods.…”
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Estimating the human height based on foot length by using Least Squares method, Runge Kutta 4th order and cubic B spline / Muhammad Abrar Izham Ajizi by Ajizi, Muhammad Abrar Izham

“…The Goodness of Fit metrics, including Mean Squares Error (MSE), Root Mean Square Error (RMSE), R-squared, Adjusted R-squared, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) were analysed to evaluate the performance of each method. …”
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Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications by Teo, Chee Huat

“…The objective evaluation includes the evaluation system of Middlebury Stereo Vision website page, computation analysis and traditional methods of Mean Square Errors (MSE), Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM). …”
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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks by Han, Fengrong, Izzeldin, Ibrahim Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue, Li, Ning

“…Besides, weighted least square method is adopted to replace the least square method to against anisotropic factors caused by irregular radio patterns. …”
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Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images by Ali Hussein Aboali, Maged Yahya

“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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Stability of Euler's method for evaluating large deformation of shear deformable plates by dual reciprocity boundary element method by Purbolaksono J., Aliabadi M.H.

“…The Euler method seems to be a more stable method for treating nonlinear problems of the shear deformable plate if the dual reciprocity method is employed to evaluate the domain integrals that appear in the formulations. � 2010 Elsevier Ltd. …”

Performance of various training algorithms on scene illumination classification by Hesamian, Mohammad Hesam, Mashohor, Syamsiah, Saripan, M. Iqbal, Wan Adnan, Wan Azizun, Hesamian, B., Hooshyari, M. M.

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Structural optimization of 4-DOF agricultural robot arm by Nurul Emylia Natasya Ahmad Zakey, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim

“…The best algorithm, i.e., the PSO algorithm, is evaluated by calculating mean square error (MSE of 0.00108527), root mean square error (RMSE of 0.01678), mean absolute error (MAE of 0.004286081), and end-effector position error (error of 0.080557045), where the best algorithm has the lowest value of error.…”
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Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

“…A single-trial extraction of a visual evoked potential (VEP) signal based on the partial least-squares (PLS) regression method has been proposed in this paper. …”
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