Zobrazeno 1 - 2
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pro vyhledávání: '"Hussain, Syed Saiq"'
Autor:
Hussain, Syed Saiq, Usman, Muhammad, Siddique, Taha Hasan Masood, Naseem, Imran, Togneri, Roberto, Bennamoun, Mohammed
In this research a novel stochastic gradient descent based learning approach for the radial basis function neural networks (RBFNN) is proposed. The proposed method is based on the q-gradient which is also known as Jackson derivative. In contrast to t
Externí odkaz:
http://arxiv.org/abs/2106.01370
Autor:
Usman, Muhammad, Ibrahim, Muhammad Sohail, Ahmad, Jawwad, Hussain, Syed Saiq, Moinuddin, Muhammad
A novel adaptive filtering method called $q$-Volterra least mean square ($q$-VLMS) is presented in this paper. The $q$-VLMS is a nonlinear extension of conventional LMS and it is based on Jackson's derivative also known as $q$-calculus. In Volterra L
Externí odkaz:
http://arxiv.org/abs/1908.02510