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1
Simulation of fast recursive least square algorithm for echo cancellation system
Published 2003“…The performance of FRLS algorithm for both filters is described and evaluated by using MATLAB software .. …”
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Student Project -
2
Improved Switching-Basedmedian Filter For Impulse Noise Removal
Published 2013“…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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Thesis -
3
Satellite attitude determination utilizing measurement sensor data and kalman filtering
Published 2006“…This assessment was done by using Monte Carlo methods to simulate these sensors. Using only star measurements an optimal satellite orientation estimate is found using the method of least squares, and the particular algorithm invoked is referred to ESOQ2 method. …”
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Article -
4
Speech enhancement based on compressive sensing algorithm
Published 2013“…The performance of overall algorithms will be evaluated based on the speech quality by optimise using informal listening test and Perceptual Evaluation of Speech Quality (PESQ). …”
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Proceeding Paper -
5
Non-fiducial based electrocardiogram biometrics with kernel methods
Published 2017“…At classification level, Gaussian multi-class Support Vector Machine (SVM) with the One-Against-All (OAA) approach is proposed to evaluate verification performance rates of the feature extraction algorithms. …”
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Thesis -
6
A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…This obviously appeared in several metrics of performance evaluation, such as accuracy of localization, node localization rate, and implementation time. …”
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Article -
7
Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…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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8
A novel computer-aided multivariate water quality index
Published 2015“…The algorithm was evaluated and demonstrated on the simulated and real datasets. …”
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Article -
9
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…Several experiments have been conducted to evaluate the performance of the proposed GA-BPNN based on the percentage of mean squared error (MSE) in learning several nonlinearity datasets. …”
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10
An efficient method of biometric matching using interpolated ECG data
Published 2010“…The ECG features are extracted from both the training dataset and the test dataset for model development and identification. Two ECG biometric algorithms which are Cross Correlation (CC) and Percent Root-Mean-Square Deviation (PRD) were used for performance evaluation. …”
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Proceeding Paper -
11
Single-trial visual evoked potential extraction using partial least-squares-based approach
Published 2016“…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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Article -
12
Single-trial visual evoked potential extraction using partial least-squares-based approach
Published 2016“…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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Article -
13
Block based low complexity iterative QR precoder structure for Massive MIMO
Published 2021“…For the system sum rate, the results of the increase in the number of users with a fixed number of 128 and 512 BS antennas show that the proposed method achieved up to 24% and 35% respectively compared to the regular BD algorithm. …”
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14
Optimized image enhancement of colour processing for retinal fundus image
Published 2025“…This approach aims to improve optimization by balancing exploration and exploitation and refining velocity control. The proposed algorithm underwent both qualitative and quantitative evaluations. …”
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15
Optimized image enhancement of colour processing for retinal fundus image
Published 2025“…This approach aims to improve optimization by balancing exploration and exploitation and refining velocity control. The proposed algorithm underwent both qualitative and quantitative evaluations. …”
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Thesis -
16
Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…Next, the weighted and transformed features were used to train Linear Discriminant Function (LDA) and to evaluate the constructed rule. The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
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Monograph -
17
Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…Moreover, various indicators were implemented to evaluate the ANN model’s productivity including relative root mean square error (RRMSE), mean square error (MSE), root mean square error (RMSE), mean absolute percentage error (MAPE) and relative error (RE). …”
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18
Color image enhancement of acute leukemia cells in blood microscopic image for leukemia detection sample
Published 2020“…The results of the proposed method are evaluated by using mean-square error (MSE), Peak-signal-to-noise-ratio (PSNR) and Absolute mean brightness error (AMBE). …”
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Conference or Workshop Item -
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Book recommendation system / Nur Dalila Afifah Ghazali
Published 2021“…By using the root mean square error to evaluate the algorithm, the result obtained shows that collaborative filtering mean error value is less than the content-based filtering. …”
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20
Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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Thesis