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

This manuscript serves a specific purpose: to give readers from fields such as material
science, chemistry, or electronics an overview of implementing a reservoir computing (RC) …

Software implementations of brain-inspired computing underlie many important
computational tasks, from image processing to speech recognition, artificial intelligence and …

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 …

Photonic neuromorphic computing is of particular interest due to its significant potential for
ultrahigh computing speed and energy efficiency. The advantage of photonic computing …

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 …

Reservoir computing is a brain-inspired machine learning framework that employs a signal-
driven dynamical system, in particular harnessing common-signal-induced synchronization …

The recognition of human actions in video streams is a challenging task in computer vision,
with cardinal applications in brain–computer interfaces and surveillance, for example …

Delay-based reservoir computing has gained a lot of attention due to the relative simplicity
with which this concept can be implemented in hardware. However, unnecessary constraints …