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MIKLÁNEK, Š.
Originální název
Analog Clipping Circuit Simulation with Recurrent Neural Networks
Typ
článek v časopise - ostatní, Jost
Jazyk
angličtina
Originální abstrakt
This article focuses on the practical use of recurrent neural networks for the simulation of analog audio circuits. Two virtual analog circuits were modeled using the Long Short-Term Memory neural networks. The neural network models presented in earlier literature were compared against newly proposed architectures, which used additional fully connected input layers. The signals processed by the neural network models of different complexity were compared to the ground truth data generated using the LTSpice software. It was found that the modifications done to the previously proposed neural network architectures can reduce the resulting prediction loss without significant increase in complexity.
Klíčová slova
recurrent neural networks, signal modeling, audio clipping circuits
Autoři
Vydáno
29. 3. 2021
Nakladatel
Elektrorevue
Místo
Brno
ISSN
1213-1539
Periodikum
Elektrorevue - Internetový časopis (http://www.elektrorevue.cz)
Ročník
23
Číslo
1
Stát
Česká republika
Strany od
Strany do
6
Strany počet
URL
http://www.elektrorevue.cz/cz/clanky/zpracovani-signalu/0/analog-clipping-circuit-simulation-with-recurrent-neural-networks/
BibTex
@article{BUT171249, author="Štěpán {Miklánek}", title="Analog Clipping Circuit Simulation with Recurrent Neural Networks", journal="Elektrorevue - Internetový časopis (http://www.elektrorevue.cz)", year="2021", volume="23", number="1", pages="1--6", issn="1213-1539", url="http://www.elektrorevue.cz/cz/clanky/zpracovani-signalu/0/analog-clipping-circuit-simulation-with-recurrent-neural-networks/" }