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  1. 1

    An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa by Md Isa, Amalina Izzati

    Published 2018
    “…Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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    Thesis
  2. 2

    Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System by Muhammad Qasim, Khan

    Published 2019
    “…Overall, robustness of the proposed algorithm is tested under different faults scenarios, taking into account several factors such as fault inception angles, line fault resistance, ground fault resistance, and the size of loads. …”
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    Thesis
  3. 3

    Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

    Published 2018
    “…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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    Thesis
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    Distinguishing Micro-Scale Voltage Disturbances Using Wavelet Decomposition Techniques by Wan, Chen Yoong

    Published 2014
    “…All the modelling and classification processes are performed in MATLAB where wavelet-1D toolbox and MATLAB algorithm are developed and employed. …”
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    Final Year Project
  7. 7

    Feature extraction of power disturbance signal using time frequency analysis by Sihab, Norsabrina

    Published 2006
    “…Power Quality has been one of the great concerns recently; it due to the increasing number of loads which sensitive to the power disturbance. One of the main issues in power quality problems includes how to localize each disturbance event and recognize its respective type of disturbance more efficiently. …”
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    Thesis