Поиск по всему репозиторию:

    • Multilayer Neural Networks Training Methodic 

      Golovko, Vladimir; Maniakov, Nikolaj; Makhnist, Leonid (Lviv polytechnic, 2003)
      Is proposed three new techniques for training of jnpUt vector If is defined as' multilayer neural networks. Its basic concept is based on the gradient descent method. For every methodic are showed formulas for calculation of the adaptive training steps. Matrix algorithmization for all of this techniques ...

      2023-12-06

    • Some Aspects of Chaotic Time Series Analysis 

      Golovko, Vladimir; Savitsky, Yury; Maniakov, Nikolaj; Rubanov, Vladimir (BSUIR, 2001)
      We address two aspects in chaotic time series analysis, namely the definition of embedding parameters and the largest Lyapunov exponent. It is necessary for performing state space reconstruction and identification of chaotic behavior. For the first aspect, we examine the mutual information for ...

      2023-11-16

    • Some Methods of Adaptive Multilayer Neural Network Training 

      Maniakov, Nikolaj; Makhnist, Leonid; Rubanov, Vladimir (BSUIR, 2003)
      Is proposed two new techniques for multilayer neural networks training. Its basic concept is based on the gradient descent method. For every methodic are showed formulas for calculation of the adaptive training steps. Matrix algorithmizations for all of these techniques are very helpful in its program ...

      2023-11-16

    • Some Methods of Adaptive Multilayer Neural Networks Training 

      Makhnist, Leonid; Maniakov, Nikolaj; Rubanov, Vladimir (2004)
      Is proposed two new techniques for multilayer neural networks training. Its basic concept is based on the gradient descent method. For every methodic are showed formulas for calculation of the adaptive training steps. Presented matrix algorithmizations for all of these techniques are very helpful ...

      2021-03-01