TY - JOUR
T1 - Nonlinear impairment compensation using neural networks
AU - Fujisawa, Shinsuke
AU - Yaman, Fatih
AU - Batshon, Hussam G.
AU - Tanio, Massaki
AU - Ishii, Naoto
AU - Huang, Chaoran
AU - de Lima, Thomas Ferreira
AU - Inada, Yoshihisa
AU - Prucnal, Paul R.
AU - Kamiya, Norifumi
AU - Wang, Ting
N1 - Publisher Copyright:
© OSA 2021, © 2021 The Author(s)
PY - 2021
Y1 - 2021
N2 - Neural networks are attractive for nonlinear impairment compensation applications in communication systems. In this paper, several approaches to reduce computational complexity of the neural network-based algorithms are presented.
AB - Neural networks are attractive for nonlinear impairment compensation applications in communication systems. In this paper, several approaches to reduce computational complexity of the neural network-based algorithms are presented.
UR - http://www.scopus.com/inward/record.url?scp=85133760420&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85133760420&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85133760420
SN - 2162-2701
JO - Optics InfoBase Conference Papers
JF - Optics InfoBase Conference Papers
T2 - Optical Fiber Communication Conference, OFC 2021
Y2 - 6 June 2021 through 11 June 2021
ER -