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  1. 1

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Testing on real data sets showed consistency results as the simulated ones. Generally, the proposed modified k-means algorithm is able to determine the optimum number of clusters for huge data.…”
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    Thesis
  2. 2

    Iterative closed-loop identification of MIMO systems using ARX-based Leaky Least Mean Square Algorithm by Rahim, M.A., Ramasamy, M., Tufa, L.D., Faisal, A.

    Published 2014
    “…The performance of the proposed algorithm with respect to the existing recursive algorithms is investigated in a simulation study. …”
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    Conference or Workshop Item
  3. 3

    Comparison of performance and computational complexity of nonlinear active noise control algorithms by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil

    Published 2011
    “…Computer simulations show that the performance of the FXLMS is more than 80% of the most effective nonlinear algorithm for each type of nonlinearity sources at the fraction of computational load. …”
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    Article
  4. 4

    An enhanced simulated kalman filter algorithm and its application in adaptive beamforming by Lazarus, Kelvin, Nurul Hazlina, Noordin, Zuwairie, Ibrahim

    Published 2019
    “…The Simulated Kalman Filter (SKF) algorithm is a newly introduced optimization algorithm inspired by the estimation capabilities of Kalman filter. …”
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    Conference or Workshop Item
  5. 5

    Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

    Published 2022
    “…The analytical results are validated through simulation. Finally, extensive simulations have been done to evaluate the performance of the proposed algorithm for various choices of optimal q-values. …”
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    Article
  6. 6

    Checkpointing in selected most fitted resource task scheduling in grid computing by Latip, Rohaya, Lew, Wai San, Chanchary, Fara Habib

    Published 2012
    “…We applied the algorithm of MeanFailure with Checkpointing in the SMF algorithm and named it MeanFailureCP-SMF. …”
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    Conference or Workshop Item
  7. 7

    MOTION PLANNING ALGORITHM FOR VEHICLE PARKING SIMULATION by Mohd Hilmi, Amirul Ehsan

    Published 2008
    “…This project focuses on creation of the motion planning algorithm of the system and developing a simulation to simulate the vehicle movements. …”
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    Final Year Project
  8. 8
  9. 9

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2022
    “…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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    Article
  10. 10

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2022
    “…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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    Article
  11. 11

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2023
    “…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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    Article
  12. 12
  13. 13

    Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia by Martono, Martono, Sudiro, Sudiro, Satino, Satino

    Published 2018
    “…The results reveals that simulation model using algorithm influences the improvement of traffic volunteers’ emergency management capabilities with p-value of < 0.05 and mean score difference of 34.5%, and the model is highly effective to be implemented to improve the capability of traffic assistant volunteers to manage trauma emergency with the mean score difference of 11.5%. …”
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    Article
  14. 14

    IMPLEMENTATION OF NOISE CANCELLATION WITH HARDWARE DESCRIPTION LANGUAGE by SUN, LEE KUANG

    Published 2006
    “…The project will focus on the implementation of adaptive filter with least-meansquares (LMS) algorithm or normalized least-mean-squares (NLMS) algorithm to cancel acoustic noises. …”
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    Final Year Project
  15. 15
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    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

    Published 2006
    “…In this paper, we combine Fuzzy C-Mean and Genetic Algorithms which are popular algorithms, the Grid can be used for scheduling. …”
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    Article
  17. 17

    Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

    Published 2016
    “…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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    Article
  18. 18

    Simulation of LMS algorithm for active noise cancellation / Ahmad Khairul Hafiz Abdullah by Abdullah, Ahmad Khairul Hafiz

    Published 2012
    “…MATLAB simulation will be used to simulate the adaptive filter to provide silent noise waveform. …”
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    Thesis
  19. 19

    Modified compound smoother in median algorithm of span size 42 / Nurul Nisa’ Khairol Azmi, Mohd Bakri Adam and Norhaslinda Ali by Khairol Azmi, Nurul Nisa’, Adam, Mohd Bakri, Ali, Norhaslinda

    Published 2019
    “…Median smoother of even window size is obtained by averaging the two middle points of arranged sequence using arithmetic mean. Some adjustments were proposed by substituting the algorithm of arithmetic mean using quadratic, geometric, harmonic and contraharmonic mean. …”
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  20. 20

    The performance of k-means clustering method based on robust principal components by Kadom, Ahmed, Midi, Habshah, Rana, Sohel

    Published 2018
    “…To remedy this problem, we proposed to integrate robust principal component analysis (RPCA) with the k-means algorithm. Simulation study and real examples are carried out to compare the performance of the classical k-means, k-means based on PCA and k-means based on RPCA. …”
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    Article