A new deep learning training method for digital back propagation (DBP) is introduced. It is invariant to polarization state rotation and phase noise. Applying the method one gains more than 1 dB over standard DBP
We propose a modified DBP algorithm accounting for PMD. The accumulated PMD at the receiver is facto...
We propose a maximum a posteriori-based scheme that extends digital backpropagation (DBP) by account...
We propose a modified DBP algorithm accounting for PMD. The accumulated PMD at the receiver is facto...
A deep learning (DL) based digital backpropagation (DBP) method with a 1 dB SNR gain over a conventi...
A computationally efficient deep learning based digital backpropagation (DL-DBP) algorithm providing...
We study a modified DBP algorithm that accounts for PMD. Based on the accumulated PMD at the receive...
We study a modified DBP algorithm that accounts for PMD. Based on the accumulated PMD at the receive...
. Digital backpropagation (DBP) is a promising digital-domain technique to mitigate Kerr-induced non...
A method for reducing the training time of a deep learning based digital backpropagation (DL-DBP) is...
In this article, we propose a model-based machine-learning approach for dual-polarization systems by...
Digital backward propagation (DBP) as a method to compensate signal distortions caused by group velo...
Despite of remarkable progress on deep learning, its hardware implementation beyond deep learning ac...
We propose a novel adaptive digital backpropagation (DBP) scheme that tracks the fiber polarization-...
An adaptive digital backward propagation (ADBP) algorithm is proposed and experimentally demonstrate...
Imaging polarimeters are a type of imaging device that attempts to estimate the polarized Stokes vec...
We propose a modified DBP algorithm accounting for PMD. The accumulated PMD at the receiver is facto...
We propose a maximum a posteriori-based scheme that extends digital backpropagation (DBP) by account...
We propose a modified DBP algorithm accounting for PMD. The accumulated PMD at the receiver is facto...
A deep learning (DL) based digital backpropagation (DBP) method with a 1 dB SNR gain over a conventi...
A computationally efficient deep learning based digital backpropagation (DL-DBP) algorithm providing...
We study a modified DBP algorithm that accounts for PMD. Based on the accumulated PMD at the receive...
We study a modified DBP algorithm that accounts for PMD. Based on the accumulated PMD at the receive...
. Digital backpropagation (DBP) is a promising digital-domain technique to mitigate Kerr-induced non...
A method for reducing the training time of a deep learning based digital backpropagation (DL-DBP) is...
In this article, we propose a model-based machine-learning approach for dual-polarization systems by...
Digital backward propagation (DBP) as a method to compensate signal distortions caused by group velo...
Despite of remarkable progress on deep learning, its hardware implementation beyond deep learning ac...
We propose a novel adaptive digital backpropagation (DBP) scheme that tracks the fiber polarization-...
An adaptive digital backward propagation (ADBP) algorithm is proposed and experimentally demonstrate...
Imaging polarimeters are a type of imaging device that attempts to estimate the polarized Stokes vec...
We propose a modified DBP algorithm accounting for PMD. The accumulated PMD at the receiver is facto...
We propose a maximum a posteriori-based scheme that extends digital backpropagation (DBP) by account...
We propose a modified DBP algorithm accounting for PMD. The accumulated PMD at the receiver is facto...
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