Open AccessNonlinear signal conversion in a formal neuron circuit
Author(s) -
Igor Bekh,
Sergey Novak
Publication year - 2021
Publication title -
transfer of innovative technologies
Language(s) - English
Resource type - Journals
eISSN - 2664-2697
pISSN - 2617-0264
DOI - 10.32347/tit2141.03011
Subject(s) - computer science , signal processing , artificial neural network , signal (programming language) , amplifier , nonlinear system , artificial intelligence , electronics , digital signal processing , computer architecture , electronic engineering , pattern recognition (psychology) , telecommunications , computer hardware , electrical engineering , engineering , bandwidth (computing) , physics , quantum mechanics , programming language
The interest in researching artificial neural networks (ARNs) is due to the fact that the method of processing information by the human brain is very different from the methods commonly used by digital computers. The brain has the ability to organize its structural components, called neurons, so that they can perform specific tasks (eg, pattern recognition, sensory signal processing, motor functions) several times faster than the fastest modern computers. [1]. At the Department of Radio Engineering and Radio-Electronic Systems of the Faculty of Radio Physics, Electronics and Computer Systems of Taras Shevchenko National University of Kyiv, a research group has been organized to build and study analog models of ANN on operational amplifiers.