Artificial neural networks for photonic applications—from algorithms to implementation: tutorial
This tutorial–review on applications of artificial neural networks in photonics targets a broad
audience, ranging from optical research and engineering communities to computer science …
audience, ranging from optical research and engineering communities to computer science …
Performance versus complexity study of neural network equalizers in coherent optical systems
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 …
several types of artificial neural networks (NNs) used for nonlinear channel equalization in …
Machine learning applications for short reach optical communication
With the rapid development of optical communication systems, more advanced techniques
conventionally used in long-haul transmissions have gradually entered systems covering …
conventionally used in long-haul transmissions have gradually entered systems covering …
Intensity-only mode decomposition on multimode fibers using a densely connected convolutional network
The use of multimode fibers offers advantages in the field of communication technology in
terms of transferable information density and information security. For applications using …
terms of transferable information density and information security. For applications using …
Feedforward and recurrent neural network-based transfer learning for nonlinear equalization in short-reach optical links
Neural network (NN)-based nonlinear equalizers have been shown effective for various
types of short-reach direct detection systems. However, they work best for a certain channel …
types of short-reach direct detection systems. However, they work best for a certain channel …
Low-complexity multi-task learning aided neural networks for equalization in short-reach optical interconnects
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 …
of neural network (NN)-based equalizers have been proposed and proved to be efficient …
High-performance end-to-end deep learning IM/DD link using optics-informed neural networks
In this paper, we introduce optics-informed Neural Networks and demonstrate
experimentally how they can improve performance of End-to-End deep learning models for …
experimentally how they can improve performance of End-to-End deep learning models for …
Machine learning-enabled intelligent fiber-optic communications: major obstacles and the way forward
FN Khan - IEEE Communications Magazine, 2022 - ieeexplore.ieee.org
Machine learning (ML) has achieved phenomenal success in revolutionizing a number of
science and engineering disciplines over the last decade. Naturally, it is also being …
science and engineering disciplines over the last decade. Naturally, it is also being …
Intra-channel nonlinearity mitigation in optical fiber transmission systems using perturbation-based neural network
In this work, a perturbation-based neural network (P-NN) scheme with an embedded
bidirectional long short-term memory (biLSTM) layer is investigated to compensate for the …
bidirectional long short-term memory (biLSTM) layer is investigated to compensate for the …
Complexity reduction over Bi-RNN-based nonlinearity mitigation in dual-pol fiber-optic communications via a CRNN-based approach
Bidirectional recurrent neural networks (bi-RNNs), in particular bidirectional long short term
memory (bi-LSTM), bidirectional gated recurrent unit, and convolutional bi-LSTM models …
memory (bi-LSTM), bidirectional gated recurrent unit, and convolutional bi-LSTM models …