We leverage the attention mechanism to investigate and comprehend the contribution of
each input symbol of the input sequence and their hidden representations for predicting the …

Nonlinear impairments caused by devices and fiber transmission links in a coherent optical
communication system can severely limit its transmission distance and achievable capacity …

Nonlinear channel impairments are a major obstacle in fiber-optic communication systems.
To facilitate a higher data rate in these systems, the complexity of the underlying digital …

We propose a bi-directional gated recurrent unit neural network based nonlinear equalizer
(bi-GRU NLE) for coherent optical communication systems. The performance of bi-GRU NLE …

Kerr nonlinearity in the form of self-and cross-phase modulation imposes a fundamental
limitation to the capacity of wavelength division multiplexed (WDM) optical communication …

We propose an efficient neural-network-based equalization jointly compensating fiber and
transceiver nonlinearities for high-symbol-rate coherent short-reach links. Providing about …

We explore recurrent and feedforward neural networks to mitigate severe inter-symbol
interference (ISI) caused by bandlimited channels, such as high speed optical …

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 …

Optical nonlinearity impairments have been a major obstacle for high-speed, long-haul and
large-capacity optical transmission. In this paper, we propose a novel convolutional neural …

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 …