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31 та иш

Иш: Using Different Features of Signal in EMG Signal Classification

  1. Сарлавҳасиз

    Бошқа1117 иқтибос
    ABI

  2. Estimation affects of formats and resizing process to the accuracy of convolutional neural network

    Muminov Bakhodir Boltaevich, Nasimov Rashid Hamid ogli, Gadoyboyeva Nigora Soibjon qizi +1

    МақолаAdvanced Neural Network Applications2019 International Conference on Information Science and Communications Technologies (ICISCT)201913 иқтибос
    ABI

  3. Localization and Classification of Myocardial Infarction Based on Artificial Neural Network

    Bahodir Muminov, Rashid Nasimov, Sanjar Mirzahalilov +2

    МақолаECG Monitoring and Analysis202012 иқтибос
    ABI

  4. Defining the Features of EMG Signals on the Forearm of the Hand Using SVM, RF, k-NN Classification Algorithms

    Adilbek Turgunov, Kudratjon Zohirov, Alisher Ganiyev +1

    МақолаMuscle activation and electromyography studies20208 иқтибос
    ABI

  5. Feature reduction and selection for EMG signal classification

    Angkoon Phinyomark, Pornchai Phukpattaranont, Chusak Limsakul

    Мақола20124 иқтибос
    ABI

  6. Surface Electromyography Signal Processing and Classification Techniques

    Rafi Hassan Chowdhury, Mamun Bin Ibne Reaz, Mohd Helmi Ali +3

    Шарҳ мақола20133 иқтибос
    ABI

  7. A Novel Feature Extraction for Robust EMG Pattern Recognition

    Angkoon Phinyomark, Chusak Limsakul, Pornchai Phukpattaranont

    Препринт20092 иқтибос
    ABI

  8. A new strategy for multifunction myoelectric control

    B. Hudgins, P. Parker, Robert N. Scott

    Мақола19932 иқтибос
    ABI

  9. Support Vector Machine-Based Classification Scheme for Myoelectric Control Applied to Upper Limb

    Mohammadreza Asghari Oskoei, Huosheng Hu

    Мақола20082 иқтибос
    ABI

  10. A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue

    Mohamed R. Al-Mulla, Francisco Sepúlveda, Martin Colley

    Шарҳ мақола20112 иқтибос
    ABI

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