Search Results - (( developing function max algorithm ) OR ( learning implementation using algorithm ))

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  1. 1

    Effective downlink resource management for wimax networks by Shareef, Zayd Ashraf Najeeb

    Published 2018
    “…Our EDRM framework involves three functions: Class-Based Scheduling (CBS) algorithm, Dynamic Bandwidth Allocation (DBA) scheme and Link Session Management (LSM) policy. …”
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    Thesis
  2. 2

    Designing and Developing an Intelligent Congkak by Muhammad Safwan, Mohd Shahidan

    Published 2011
    “…and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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    Thesis
  3. 3

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

    Published 2019
    “…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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    Thesis
  4. 4

    Adaptive resource allocation algorithms with QoS support in OFDMA-based WiMAX networks by Alsahag, Ali Mohamemed Mansor

    Published 2014
    “…The aim of this thesis is to develop a fair and effi- cient packet scheduling and adaptive multiuser frequency-time domain resources allocation algorithms to support QoS for a diverse service class in OFDMA based IEEE 802.16 network. …”
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    Thesis
  5. 5

    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

    Published 2023
    “…GA assists in optimizing the search process and performs machine learning. Within the GA, nearest neighbor algorithm is used in determining the most similar recorded case that can be used in solving the new case. …”
    Conference paper
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    Design And Implementation Of Low Passband Ripple Digital Down Converter Filter For Software Defined Radio Transceiver by Naghmash, Majid Salal

    Published 2011
    “…The proposed DDC filters incorporate of Remez algorithm and Mini-max algorithm to reduce the error rate in the filter response. …”
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    Thesis
  7. 7

    DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES by HANIZAM, MOHD HAZIQ NAZMI

    Published 2019
    “…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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    Final Year Project
  8. 8

    Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

    Published 2021
    “…In this paper, object detection model is developed and implemented with deep learning algorithm. Object classification model is produced through the model training with Deep Neural Networks (DNN). …”
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    Proceedings
  9. 9

    Development of low power viterbi decoder on complex programmable logic device platform by Abu, Mohd Azlan

    Published 2018
    “…Consequently, the number of logic gates and the total power consumption of the STTC Viterbi decoder can be reduced by using the new algorithms. The proposed algorithms have been designed and implemented by using MATLAB, Altera Quartus 2 and Altera MAX V CPLD board. …”
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    Thesis
  10. 10

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
    “…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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    Conference or Workshop Item
  11. 11

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

    Published 2020
    “…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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    Conference or Workshop Item
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    MBIST implementation and evaluation in FPGA based on low-complexity March algorithms by Jidin, Aiman Zakwan, Mispan, Mohd Syafiq, Hussin, Razaidi, Weng, Fook Lee

    Published 2024
    “…They were implemented in the Intel Max 10 DE10-Lite FPGA Development Board. A test generator was built in FPGA, as an alternative to the external tester, to provide test vectors required in initiating the test on the memory model using the implemented MBIST. …”
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    Article
  14. 14

    Object based segmentation and analysis using deep learning algorithm for cats and dogs images by N.Rajandhiran, Shreevishal

    Published 2023
    “…The deep learning algorithm implemented is the Unet architecture and the Segnet architecture respectively. …”
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    Final Year Project / Dissertation / Thesis
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    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
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    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…In the cycle of Industrial Revolution 4.0 (IR 4.0), many issues in the industries can be solved with implementation of artificial intelligence approaches, including machine learning models. …”
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    Conference or Workshop Item
  18. 18

    CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS by TEH, CHOON KEONG

    Published 2017
    “…Therefore, this project introduces three learning algorithms which are Extreme Learning Machine (ELM), Finite Impulse Response Extreme Learning Machine (FIR-ELM) and Discrete Fourier Transform Extreme Learning Machine (DFT-ELM) to improve the bearing fault diagnosis accuracy and shorten the time used to train and test the neural network.…”
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    Final Year Project
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    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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    Article