M Li, W Zhang, Q Chen, Z He - Optics Letters, 2021 - opg.optica.org
Hardware implementation of neural network based nonlinear equalizers will encounter tremendous challenges due to a high-throughput data stream and high computational …
The deployment of artificial neural networks-based optical channel equalizers on edge- computing devices is critically important for the next generation of optical communication …
PJ Freire, A Napoli, B Spinnler… - Journal of Lightwave …, 2023 - ieeexplore.ieee.org
This paper introduces a novel methodology for developing low-complexity neural network (NN) based equalizers to address impairments in high-speed coherent optical transmission …
Z Xu, S Dong, JH Manton, W Shieh - Journal of Lightwave …, 2022 - opg.optica.org
With the rapid development of machine learning technologies in recent years, different types of neural network (NN)-based equalizers have been proposed and proved to be efficient …
The computational complexity and system bit-error-rate (BER) performance of four types of neural-network-based nonlinear equalizers are analyzed for a 50-Gb/s pulse amplitude …
This paper performs a detailed, multi-faceted analysis of key challenges and common design caveats related to the development of efficient neural networks (NN) based nonlinear …
We present the results of the comparative performance-versus-complexity analysis for the several types of artificial neural networks (NNs) used for nonlinear channel equalization in …
In this work, we demonstrate the offline FPGA realization of both recurrent and feedforward neural network (NN)-based equalizers for nonlinearity compensation in coherent optical …
B Sang, W Zhou, Y Tan, M Kong, C Wang… - Journal of Lightwave …, 2022 - opg.optica.org
Nowadays, Neural network (NN) has been proved to be an effective solution for nonlinear equalization in short reach optical systems. However, recent research has mainly focused …