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  1. 1

    An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, Sali, Aduwati, A. Rasid, Mohd Fadlee, Mohamad, Hafizal

    Published 2017
    “…Simulation results show convergence and adaptability of the algorithm to dynamic environment in achieving optimal solutions. …”
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    Article
  2. 2

    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

    Published 2016
    “…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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    Thesis
  3. 3

    Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm by Mehrkanoon, S., Moghavvemi, M., Fariborzi, H.

    Published 2007
    “…Proposed method uses horizontal EOG (HEOG), vertical EOG (VEOG), and EMG signals as three reference digital filter inputs. …”
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  4. 4

    Self-tuning control of an electro-hydraulic actuator system by Ghazali, Rozaimi, Md Sam, Yahaya, Rahmat, Mohd Fua'ad, Jusoff, Kamaruzaman, Zulfatman, Mohd Hashim, Abd Wahab Ishari

    Published 2011
    “…Due to time-varying effects in electro-hydraulic actuator (EHA) system parameters, a self-tuning control algorithm using pole placement and recursive identification is presented. …”
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  5. 5

    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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    Thesis
  6. 6

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…In the simulation the robot is equipped with thirteen distance sensing sensors. From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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  7. 7

    The Effects Of Weightage Values With Two Objective Functions In iPSO For Electro-Hydraulic Actuator System by Ghazali, Rozaimi, Ghani, Muhamad Fadli, Chai, Mau Shern, Chong, Shin Horng, Chong, Chee Soon, Md Sam, Yahaya, Has, Zulfatman

    Published 2021
    “…The PID controller parameters will be tuned by using the iPSO algorithm to get the lowest overshoot percentage and steady-state error. …”
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  8. 8
  9. 9

    Classical and metaheuristic optimizations performance in an electro-hydraulic control system by Chong, Chee Soon, Ghazali, Rozaimi, Chong, Shin Horng, Ghani, Muhammad Fadli, Md. Sam, Yahaya, Has, Zulfatman

    Published 2022
    “…A classical and metaheuristic optimization methods, which are gradient descent (GD) and particle swarm optimization (PSO) algorithm are used to obtaining the optimal gains of both controllers. …”
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  10. 10

    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

    Published 2025
    “…Current FDD technologies mostly rely on data-driven solutions by making full use of abundant process data collected by the state-of-the-art distributed process instruments and sensors. Deep learning algorithms were widely used among all the data-driven algorithms. …”
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  11. 11

    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
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  12. 12

    Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System by Muhammad Nasir, Mohd Nizar, Mohd Nordin, Najaa Aimi, Mohd Faudzi, Ahmad Athif, Muftah, Mohamed Naji, Mhd Yusoff, Mohd Akmal, Shahrol Mohamaddan, Shahrol Mohamaddan

    Published 2023
    “…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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  13. 13

    Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System by Muhammad Nasir, Mohd Nizar, Mohd Nordin, Ili Najaa Aimi, Mohd Faudzi, Ahmad Athif, Muftah, Mohamed Naji, Mhd Yusoff, Mohd Akmal, Shahrol Mohamaddan, Shahrol Mohamaddan

    Published 2023
    “…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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    Article
  14. 14

    Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System by Muhammad Nasir, Mohd Nizar, Mohd Nordin, Najaa Aimi, Mohd Faudzi, Ahmad Athif, Muftah, Mohamed Naji, Mhd Yusoff, Mohd Akmal, Mohamaddan, Shahrol

    Published 2023
    “…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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    Article
  15. 15

    Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System by Muhammad Nasir, Mohd Nizar, Mohd Nordin, Ili Najaa Aimi, Mohd Faudzi, Ahmad Athif, Muftah, Mohamed Naji, Mhd Yusoff, Mohd Akmal, Mohamaddan, Shahrol

    Published 2023
    “…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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    Article
  16. 16

    Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System by Muhammad Nasir, Mohd Nizar, Mohd Nordin, Najaa Aimi, Mohd Faudzi, Ahmad Athif, Muftah, Mohamed Naji, Mhd Yusoff, Mohd Akmal, Mohamaddan, Shahrol

    Published 2023
    “…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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    Article
  17. 17

    Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System by Muhammad Nasir, Mohd Nizar, Mohd Nordin, Najaa Aimi, Mohd Faudzi, Ahmad Athif, Muftah, Mohamed Naji, Mhd Yusoff, Mohd Akmal, Mohamaddan, Shahrol

    Published 2023
    “…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
    Get full text
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    Article
  18. 18

    Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System by Muhammad Nasir, Mohd Nizar, Mohd Nordin, Najaa Aimi, Mohd Faudzi, Ahmad Athif, Muftah, Mohamed Naji, Mhd Yusoff, Mohd Akmal, Mohamaddan, Shahrol

    Published 2023
    “…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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    Article
  19. 19

    Normalized SPSA for Hammerstein model identification of twin rotor and electro-mechanical positioning systems by Nik Mohd Zaitul Akmal, Mustapha, Mohd Ashraf, Ahmad

    Published 2025
    “…The effectiveness of the proposed method was validated by modeling the actual systems, which included the twin-rotor system (TRS) and the electro-mechanical positioning system (EMPS). …”
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  20. 20