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  1. 1
    Iterative closed-loop identification of MIMO systems using ARX-based Leaky Least Mean Square Algorithm

    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
    “…Closed-loop identification of MIMO systems is considered. An iterative Leaky Least Mean Squares (LLMS) algorithm is proposed for the development of ARX structure. …”
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  2. 2
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  3. 3
    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

    Published 2017
    “…All the proposed algorithms are demonstrated with the help of extensive simulation case studies and a real pilot-scale distillation column with appropriate validation procedures.…”
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  4. 4
    Adaptive Linear System Identification over Simulated Wireless Environment

    Adaptive Linear System Identification over Simulated Wireless Environment by Elamin, Musab Jabralla Omer Elamin

    Published 2009
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  5. 5
    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali

    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali by Mohd Razali, Ainaa Farhanah

    Published 2022
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  6. 6
    Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering

    Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering by Umelo, Nnamdi Henry, Noordin, Nor Kamariah, A. Rasid, Mohd Fadlee, Tan, Kim Geok, Hashim, Fazirulhisyam

    Published 2023
    “…Existing works do not provide readers prior tag estimates. Most algorithms assume a collision slot means two tag collision. …”
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  7. 7
    System identification using Extended Kalman Filter

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…System identification is getting more intensive from researcher to develop an algorithm with work efficiently and more accurate. …”
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  8. 8
    Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani

    Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani by Seyed Asadollah, Abdiesfandani

    Published 2016
    “…The algorithm simulates two important tasks that are frequently used by the human experts to identify summarizing strategies used to produce the summary sentences: 1) sentences relevance identification; and 2) summarizing strategies identification. …”
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  9. 9
    Grouping based radio frequency identification anti-collision protocols for dense internet of things application

    Grouping based radio frequency identification anti-collision protocols for dense internet of things application by Umelo, Nnamdi H., Noordin, Nor K., A. Rasid, Mohd Fadlee, Geok, Tan K., Hashim, Fazirulhisyam

    Published 2022
    “…The algorithms were implemented in MATLAB while extensive Monte Carlo simulation was performed to evaluate their strengths and weaknesses. …”
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  10. 10
    A novel quantum calculus-based complex least mean square algorithm (q-CLMS)

    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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  11. 11
    A novel quantum calculus-based complex least mean square algorithm (q-CLMS)

    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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  12. 12
    A novel quantum calculus-based complex least mean square algorithm (q-CLMS)

    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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  13. 13
    Modeling of widely-linear quaternion valued systems using hypercomplex algorithms

    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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  14. 14
    Parametric system identification and active vibration control of vibrational structures using genetic algorithm

    Parametric system identification and active vibration control of vibrational structures using genetic algorithm by Mohammad Sofi @ Aziz, Azfi Zaihan

    Published 2007
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  15. 15
    Fuzzy voice classifier and fuzzy voice pathology identification system

    Fuzzy voice classifier and fuzzy voice pathology identification system by Sathees Kumar, Nataraj, Sazali, Yaacob, Prof. Dr., Ahamad Nazri, Abdullah

    Published 2012
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  16. 16
    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm

    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq

    Published 2024
    “…The unified RBF model is then used for autotuning the PID controller using the DE algorithm. The proposed RBF-NN system identification can successfully predict the attitude dynamics of a quadplane in all flight modes with a coefficient of determination of R2 greater than 0.9 and a computing mean time of less than 5 ms. …”
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  17. 17
    Recursive least square and fuzzy modelling using genetic algorithm for process control application

    Recursive least square and fuzzy modelling using genetic algorithm for process control application by Abdul Rahman, Ribhan Zafira, Yusof, Rubiyah, Khalid, Marzuki

    Published 2007
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  18. 18
    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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  19. 19
    System Identification And Control Of Automatic Car Pedal Pressing System For Low-Speed Driving In A Road Traffic Delay

    System Identification And Control Of Automatic Car Pedal Pressing System For Low-Speed Driving In A Road Traffic Delay by Lai, Chong Jin

    Published 2022
    “…The controller gains were tuned using metaheuristic algorithm which is Particle Swarm Algorithm (PSO) for optimal values of fuzzy controller parameters. …”
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  20. 20
    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm

    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Yaakub, Mohd Fauzi

    Published 2024
    “…The unified RBF model is then used for autotuning the PID controller using the DE algorithm. The proposed RBF-NN system identification can successfully predict the attitude dynamics of a quadplane in all flight modes with a coefficient of determination of R2 greater than 0.9 and a computing mean time of less than 5 ms. …”
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