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    • 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

    • On the Binary Sequences with Indistinguishable Signature for a Given Error Multiplicity in Electronic Testing 

      Demidenko, Serge; Ivanyukovich, Alexander; Makhnist, Leonid; Piuri, Vincenzo (Journal of The Institution of Engineers, Singapore, 1995)
      Distinct binary seąuences (2 ͫ – 1 bits long) may be compressed by an m-bit signature register into the same signature ualue, when a given error multiplicity is considered. Analytical expressions to compute the number of distinct seąuences collapsed into the same signature are presented, by exploiting ...

      2022-02-18

    • 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