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  1. 1
    An amplitude independent muscle activity detection algorithm based on adaptive zero crossing technique and mean instantaneous frequency of the sEMG signal

    An amplitude independent muscle activity detection algorithm based on adaptive zero crossing technique and mean instantaneous frequency of the sEMG signal by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina

    Published 2017
    “…This new feature in addition to the mean of the Mean Instantaneous Frequency (MMIF) of the signal is used to detect the presence of the muscle activities in the sEMG signals.…”
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  2. 2
    Comparison of performance and computational complexity of nonlinear active noise control algorithms

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

    Published 2011
    “…Research on nonlinear active noise control (NANC) revolves around the investigation of the sources of nonlinearity as well as the performance and computational load of the nonlinear algorithms. …”
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  3. 3
    All-pass filtered x least mean square algorithm for narrowband active noise control

    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

    Published 2018
    “…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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  4. 4
    A near-optimal centroids initialization in K-means algorithm using bees algorithm

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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  5. 5
    Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity

    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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  6. 6
    Simulation of LMS algorithm for active noise cancellation / Ahmad Khairul Hafiz Abdullah

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

    Published 2012
    “…An active noise control is used adaptive filter to reduce noise. …”
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  7. 7
    Clustering chemical data set using particle swarm optimization based algorithm

    Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

    Published 2008
    “…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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  8. 8
    Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity

    Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity by Dehkordi, Sepehr Ghasemi

    Published 2014
    “…An active method which has received much attention is the use of Active Noise Control (ANC) system which involves an electro acoustic system that cancels unwanted noise using the principle of superposition. …”
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  9. 9
    Real time nonlinear filtered-x lms algorithm for active noise control

    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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  10. 10
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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  11. 11
    Simulation of LMS algorithm for active noise cancellation: article / Ahmad Khairul Hafiz Abdullah

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

    Published 2012
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  12. 12
    Cluster optimization in VANET using MFO algorithm and K-Means clustering

    Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

    Published 2023
    “…Improving clustering efficiency by sending frequent updates to the CH in term of improving scalability, coverage, and clustering result, while reducing communication and energy consumption. Overall, the MFO Algorithm and K-Means algorithm can be used in combination to optimize the clustering in VANET, leading to better network performance, more reliable communication, and improved efficiency.…”
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  13. 13
    Performance comparison of THF-NLFXLMS and VFXLMS algorithms for Hammerstein NANC

    Performance comparison of THF-NLFXLMS and VFXLMS algorithms for Hammerstein NANC by Srazhidinov, Radik, Raja Ahmad, Raja Mohd Kamil

    Published 2016
    “…Recently, THF-NLFXLMS algorithm was developed to compensate the nonlinearity encountered in nonlinear active noise control systems. …”
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  14. 14
    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds

    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
    “…The results of the algorithm show significant improvement in comparison to a similar implementation of the hard c-means algorithm.…”
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  15. 15
    Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity

    Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity by Ghasemi, Sepehr, Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

    Published 2016
    “…Adaptive algorithms are prevalently applied in the design of nonlinear active noise control (ANC) systems. …”
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  16. 16
    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm

    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm by Mohd Sharif, Sharifah, Mohd Kusin, Faradiella, Asha’ari, Zulfa Hanan, Aris, Ahmad Zaharin

    Published 2015
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  17. 17
    A modified π rough k-means algorithm for web page recommendation system

    A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

    Published 2018
    “…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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  18. 18
    Noise Cancellation method in assistive listening system

    Noise Cancellation method in assistive listening system by Noor Aliff, Noor Affande

    Published 2020
    “…Those algorithms were Least Means Square, Normalize-Least Means Square, Recursive Least Square, Simple SetMembership Algorithm and Dynamic Set-Membership Affine Projection Algorithm. …”
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  19. 19
    An Improved Wavelet Neural Network For Classification And Function Approximation

    An Improved Wavelet Neural Network For Classification And Function Approximation by Ong , Pauline

    Published 2011
    “…First, the types of activation functions used in the hidden layer of the WNN were varied. …”
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  20. 20
    HYBRID ALGORITHM FOR HAND GESTURE RECOGNITION USING LOCAL GABOR FILTER AND MEL FREQUENCY CEPSTRAL COEFFICIENTS

    HYBRID ALGORITHM FOR HAND GESTURE RECOGNITION USING LOCAL GABOR FILTER AND MEL FREQUENCY CEPSTRAL COEFFICIENTS by GUPTA, SHIKHA

    Published 2014
    “…Hand gesture is a movement ofhands having meaning to speak, with other people. However, using hand gestures as a medium for communication requires correct recognition of indeed pose and due to this, hand gesture recognition is an active area of research in the vision community. …”
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