Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …

We review a novel paradigm that has emerged in analogue neuromorphic optical
computing. The goal is to implement a reservoir computer in optics, where information is …

Reservoir computing is a relatively recent computational paradigm that originates from a
recurrent neural network and is known for its wide range of implementations using different …

The rapid development of artificial intelligence (AI) facilitates various applications from all
areas but also poses great challenges in its hardware implementation in terms of speed and …

Time-delayed optoelectronic oscillators are at the center of a large body of scientific
literature. The complex behavior of these nonlinear oscillators has been thoroughly explored …

Deep learning has been revolutionizing information processing in many fields of science
and engineering owing to the massively growing amounts of data and the advances in deep …

The concept of reservoir computing emerged from a specific machine learning paradigm
characterized by a three-layered architecture (input, reservoir, and output), where only the …

High-speed photonic reservoir computing (RC) has garnered significant interest in
neuromorphic computing. However, existing reservoir layer (RL) architectures mostly rely on …

Existing work on coherent photonic reservoir computing (PRC) mostly concentrates on
single-wavelength solutions. In this paper, we discuss the opportunities and challenges …

This paper proposes and demonstrates a model for generating microwave waveforms using
a delay feedback photonic reservoir computing system with SOA. Our scheme involves …