Name
Title | ||
|---|---|---|
Accelerating the Learning Speed of DNN Equalizer in Underwater VLC System by an Auxiliary Kernel Layer |
Abstract | ||
|---|---|---|
We compared various kernel-aided deep neural network (K-DNN) equalizers, which can significantly reduce the iterative training times (ITTs) of the deep neural network (DNN) nonlinear equalizer. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICT.2019.8798820 | 2019 26th International Conference on Telecommunications (ICT) |
Keywords | Field | DocType |
Visible light communication,Deep neural networks,Equalizer | Kernel (linear algebra),Equalizer,Nonlinear system,Computer science,Real-time computing,Visible light communication,Electronic engineering,Artificial neural network,Deep neural networks,Underwater | Conference |
ISBN | Citations | PageRank |
978-1-7281-0274-0 | 0 | 0.34 |
References | Authors | |
3 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| N. Chi | 1 | 13 | 12.49 |
| Yiheng Zhao | 2 | 1 | 1.06 |