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Proceedings ArticleDOI

Computational-Complexity Comparison of Artificial Neural Network and Volterra Series Transfer Function for Optical Nonlinearity Compensation with Time- and Frequency-Domain Dispersion Equalization

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TLDR
The results show that the ANN involved lower computational complexity than the VSTF when additional time-domain nonlinear processing is required.
Abstract
We evaluated the number of complex multiplications in an ANN and a VSTF for optical nonlinearity compensation. The results show that the ANN involved lower computational complexity than the VSTF when additional time-domain nonlinear processing is required.

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Journal ArticleDOI

A Simple Joint Modulation Format Identification and OSNR Monitoring Scheme for IMDD OOFDM Transceivers Using K-Nearest Neighbor Algorithm

TL;DR: Experimental results show that five common quadrature amplitude modulation (QAM) modulation formats can be identified and system OSNR monitoring can be achieved and the average prediction mean square error is similar to that using an artificial neural network.
Journal ArticleDOI

IM/DD mode division multiplexing transmission enabled by machine learning-based linear and nonlinear MIMO equalization

TL;DR: Two mode division multiplexing transmission systems through few-mode fiber by using two degenerate LP11 modes in high speed and low cost optical interconnection scenarios are demonstrated and two novel MIMO equalizers based on machine learning are proposed and utilized to eliminate the impairments.
Journal ArticleDOI

Deep Neural Network Based Chromatic Dispersion Estimation With Ultra-Low Sampling Rate for Optical Fiber Communication Systems

TL;DR: A novel CD estimation method based on the deep neural network (DNN) with ultra-low sampling rate is proposed for the optical fiber transmission systems and shows great potential for the cost-effective under-sampled systems.
Proceedings ArticleDOI

Overfitting of ANN-based Nonlinear Equalizer for Multilevel Signals in Optical Communication Systems

TL;DR: The results show that Gray coding works to relax the condition which causes the overfitting of ANN-based nonlinear equalizer for multilevel optical signals generated by PRBS.
Proceedings ArticleDOI

Polarization Tracking and Optical Nonlinearity Compensation Using Artificial Neural Networks

TL;DR: A novel polarization-tracking scheme using an artificial neural network (ANN), which can compensate nonlinear waveform distortion at the same time, is proposed, comparing with FIR filters.
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