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 …

For the first time, multi-task learning is proposed to improve the flexibility of NN-based
equalizers in coherent systems. A" single" NN-based equalizer improves Q-factor by up to 4 …

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 …

In recent years, extensive research has been conducted to explore the utilization of machine
learning algorithms in various direct-detected and self-coherent short-reach communication …

Low-cost Coherent Transceivers with Quantization Noise Mitigation Function Enabled by Neural
Networks Page 1 Low-cost Coherent Transceivers with Quantization Noise Mitigation Function …

Next generation DCI/DCN reaches 800Gb/s. Distances up to 10km make chromatic
dispersion the bottleneck for O-band PAM4 CWDM4. Neural network equalizers provide …

We compare hardware parallelization of CD equalizers on 10 km 4x200 Gb/s IM/DD PAM4
O-band measurements. A single neural network equalizer with multiple output symbols …

We propose to use symbol decision based on neural networks to alleviate the impacts of
quantization noise, laser phase noise, IQ impairments, and their interactions. Our DSP …

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