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  1. 1

    Modeling of widely-linear quaternion valued systems using hypercomplex algorithms by Mohammed, Haydar Imad, Hashim, Fazirulhisyam, Che Ujang, Che Ahmad Bukhari

    Published 2015
    “…The data-driven optimal modeling and identification of widely-linear quaternion-valued synthetic systems is achieved by using a quaternion-valued gradient based algorithms. …”
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    Conference or Workshop Item
  2. 2

    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

    Published 2017
    “…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
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    Thesis
  3. 3

    Enhanced Automated Framework For Cattle Tracking And Classification by Williams, Bello Rotimi

    Published 2022
    “…An enhanced object tracking algorithm (PFtmM) that integrates enhanced particle filter algorithm (PFtm) with mean-shift tracker (M) is proposed and deployed as first step to address the problems arise due to occurrence of occlusion and non-linear movement of cow objects in video. …”
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    Thesis
  4. 4

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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    Thesis
  5. 5

    Adaptive beamforming with 16 element linear array using MaxSIR and MMSE algorithms by Islam, Md. Rafiqul, Hafriz, Fahmy, Norfauzi, Muhammad

    Published 2007
    “…Maximum Signal-to-Interference Ratio (MaxSIR) and Minimum Mean Square Error (MMSE) beamforming algorithms were investigated using 16 elements linear array antenna. …”
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    Proceeding Paper
  6. 6

    Clustering Spatial Data Using a Kernel-Based Algorithm by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2005
    “…Finally, we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering spatial data as a case study. …”
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    Conference or Workshop Item
  7. 7

    Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

    Published 2012
    “…Furthermore, the modeling of the THF can be realized using least mean square (LMS) algorithm and utilized in the NLFXLMS control scheme. …”
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    Article
  8. 8

    Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

    Published 2021
    “…The performance was benchmarked using root mean squared error (RMSE), mean absolute error (MAE), Coefficient of Determination (R2 ), mean absolute percentage error (MAPE) and Global Performance Index (GPI) as well as their time cost. …”
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    Final Year Project / Dissertation / Thesis
  9. 9

    An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

    Published 2022
    “…The higher the TERR threshold value is set, the more the feature subset size will be, regardless of the type of clustering algorithm and the clustering evaluation criterion are used. …”
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    Book Chapter
  10. 10
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  12. 12

    Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

    Published 2012
    “…The performance of these algorithms is usually compared with the standard linear filtered-x least mean square (FXLMS) algorithm. …”
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    Thesis
  13. 13

    Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network by Md Akib, Afif, Saad, Nordin, Asirvadam, Vijanth

    Published 2011
    “…Relative mass released of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithms for updating the linear weight. Radial basis function (RBF) is used to define the non-linear weight of the partial linear network. …”
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    Book Section
  14. 14

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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    Article
  15. 15

    Missing value estimation methods for data in linear functional relationship model by Adilah Abdul Ghapor, Yong Zulina Zubairi, A.H.M. Rahmatullah Imon

    Published 2017
    “…The performance of EM and EMB are measured using mean absolute error, root-mean-square error and estimated bias. …”
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    Article
  16. 16

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…Filtered-X least mean square (FXLMS) control algorithm is a conventional algorithm employed to cancel the noise in linear environment. …”
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    Thesis
  17. 17

    Enhancement of Space-Time Receiver Structure with Multiuser Detection for Wideband CDMA Communication Systems by Subramaniam, Jeevan Rao

    Published 2006
    “…We consider two different pilot symbol assisted adaptive beamforming algorithms, Least Mean Square (LMS) and Recursive Least Square (RLS). …”
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    Thesis
  18. 18

    Dynamic determinant matrix-based block cipher algorithm by Juremi, Julia

    Published 2018
    “…For the avalanche effect analysis, the DDBC algorithm shows that most of the correlation values tested on the proposed determinant s-boxes and the RotateSwapDeterminant function are near to 0 which indicate a strong positive (or negative) non-linear relationship which means the DDBC algorithm has a high confusion property. …”
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    Thesis
  19. 19

    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

    Published 2012
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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    Article
  20. 20

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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    Article