The ability to interpret information through automatic sensors is one of the most important
pillars of modern technology. In particular, the potential of biosensors has been used to …

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 …

Experimental results based on offline processing reported at optical conferences
increasingly rely on neural network-based equalizers for accurate data recovery. However …

Fiber nonlinearity is one of the major impairments for long-haul transmission systems.
Therefore, estimating the nonlinear signal-to-noise ratio (SNR_NL) is indispensable to …

A self-supervised learning scheme is proposed for neural-network-based perturbative fiber
nonlinearity compensation with a designed proxy task by using phase-conjugated unknown …

Low-Complexity Efficient Neural Network Optical Channel Equalizers: Training, Inference, and
Hardware Synthesis Page 1 Low-Complexity Efficient Neural Network Optical Channel …

Nowadays, the demand for telecommunication services is rapidly growing. To meet this
everincreasing connectivity demand telecommunication industry needs to maintain the …