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10 та иш

Иш: Classification Of Some Sensitive Motion Of Fingers To Create Modern Biointerface

  1. Comparative Analysis of the Results of EMG Signal Classification Based on Machine Learning Algorithms

    Adilbek Turgunov, Kudratjon Zohirov, Rashid Nasimov +1

    МақолаMuscle activation and electromyography studies2021 International Conference on Information Science and Communications Technologies (ICISCT)20218 иқтибос
    ABI

  2. 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

  3. A new dataset for the detection of hand movements based on the SEMG signal

    Adilbek Turgunov, Kudratjon Zohirov, Bobur Muhtorov

    МақолаEEG and Brain-Computer Interfaces20207 иқтибос
    ABI

  4. Using Different Features of Signal in EMG Signal Classification

    Adilbek Turgunov, Kudratjon Zohirov, Shamiljon Rustamov +1

    МақолаMuscle activation and electromyography studies2020 International Conference on Information Science and Communications Technologies (ICISCT)20206 иқтибос
    ABI

  5. Feature reduction and selection for EMG signal classification

    Angkoon Phinyomark, Pornchai Phukpattaranont, Chusak Limsakul

    Мақола20124 иқтибос
    ABI

  6. Brain–computer interfaces for communication and control

    Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland +2

    Шарҳ мақола20023 иқтибос
    ABI

  7. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  8. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  9. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  10. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI