Your browser doesn't support javascript.

Biblioteca Virtual em Saúde

Brasil

Home > Pesquisa > ()
Imprimir Exportar

Formato de exportação:

Exportar

Email
Adicionar mais destinatários
| |

Gaussian kernel-aided deep neural network equalizer utilized in underwater PAM8 visible light communication system.

Chi, Nan; Zhao, Yiheng; Shi, Meng; Zou, Peng; Lu, Xingyu.
Opt Express; 26(20): 26700-26712, 2018 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-30469751
In this paper, we demonstrate a novel Gaussian kernel-aided deep neural network (GK-DNN) equalizer that can effectively compensate for the high nonlinear distortion of underwater PAM8 visible light communication (VLC) channels. The application of a Gaussian kernel can reduce the necessary training iterations to 47.06%, enabling it to outperform the traditional DNN equalizer. At the same time, a novel design strategy with respect to the structure of the GK-DNN equalizer is proposed, which can effectively save computing resources and reduce the data volume of the necessary training data set. By using the GK-DNN equalizer, a 1.5 Gbps PAM8 VLC system over 1.2-m underwater transmission is successfully demonstrated.
Selo DaSilva