Search Results - (( using function learning algorithm ) OR ( parallel implementation phase algorithm ))

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  1. 1

    Distributed generation system using parallel inverters supplied by unstable DC source by Younis, M.A.A., Rahim, N.A., Mekhilef, Saad

    Published 2009
    “…The generation of control algorithm for three-phase inverter is implemented in Digital Signal Processing (DSP) boards. …”
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    Article
  2. 2

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…A comparative study is done to validate the proposed algorithm by implementing the other contemporary algorithms for the same dataset. …”
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  3. 3

    Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

    Published 2018
    “…The proposed implementation shown significant speedups of 11Ã� and 5Ã� compared to the sequential and parallel CPU implementations respectively. …”
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  4. 4

    Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

    Published 2018
    “…The proposed implementation shown significant speedups of 11Ã� and 5Ã� compared to the sequential and parallel CPU implementations respectively. …”
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    Article
  5. 5

    Three phase induction motor coupled to DC motor in hybrid electric vehicle application by Zulkarnain, Lubis

    Published 2011
    “…The new on-line parameter adaptation algorithm has been tested experimentally on three phase induction machine for a proof-of-concept demonstration. …”
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    Thesis
  6. 6

    FPGA implementation of CPFSK modulation techniques for HF data communication by Jaswar, Fitri Dewi, Sha'ameri, Ahmad Zuri

    Published 2003
    “…Further reduction in components is achieved hy adopting a multiplierless and parallel algorithm at the receiver module. This is proven by comparing with conventional noncoherent detection algorithm.…”
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    Conference or Workshop Item
  7. 7

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…The hybrid algorithm was implemented to minimise the length of time needed to address the massive scale of the detected parallel power load abnormalities. …”
    Article
  8. 8

    Multistring five-level inverter with novel PWM control scheme for PV application by Rahim, N.A., Selvaraj, J.

    Published 2010
    “…DSP TMS320F2812 is used to implement this PWM switching scheme together with a digital proportional-integral current control algorithm. …”
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    Article
  9. 9

    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…However, present complex algorithms which are accurate require high processing power using a large size of learning dataset without labelling error. …”
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    Thesis
  10. 10

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
    “…Functional Link Neural Network (FLNN) has becoming as an important tool used in machine learning due to its modest architecture. …”
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  11. 11
  12. 12

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    Published 2016
    “…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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    Thesis
  13. 13

    Design and implementation of multimedia digital matrix system by Chui, Yew Leong, Ramli, Abdul Rahman, Perumal, Thinagaran, Sulaiman, Mohd Yusof, Ali, Mohd Liakot

    Published 2005
    “…Due to the issues of signal integrity in high-speed digital design, a new adaptive channel synchronization algorithm has been developed. The algorithm, named as hybrid-reset algorithm utilizes the nature of asynchronous reset to compensate the drawback of synchronous counter for phase detection. …”
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    Conference or Workshop Item
  14. 14

    A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

    Published 2006
    “…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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    Proceeding Paper
  15. 15

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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  16. 16

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
    Article
  17. 17

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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    Thesis
  18. 18

    Dynamic training rate for backpropagation learning algorithm by Al-Duais, M. S., Yaakub, Abdul Razak, Yusoff, Nooraini

    Published 2013
    “…In this paper, we created a dynamic function training rate for the Back propagation learning algorithm to avoid the local minimum and to speed up training.The Back propagation with dynamic training rate (BPDR) algorithm uses the sigmoid function.The 2-dimensional XOR problem and iris data were used as benchmarks to test the effects of the dynamic training rate formulated in this paper.The results of these experiments demonstrate that the BPDR algorithm is advantageous with regards to both generalization performance and training speed. …”
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    Conference or Workshop Item
  19. 19

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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    Thesis
  20. 20

    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…Backpropagation (BP) algorithm is widely used to solve many real world problems by using the concept of Multilayer Perceptron (MLP). …”
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    Thesis