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

Reservoir computing (RC) is a neural computing paradigm especially well-suited for
learning dynamical systems by leveraging an untrained reservoir layer, providing high …

Reservoir computing (RC) is a computational architecture capable of efficiently processing
temporal information, which allows low-cost hardware implementation. However, the …

Reservoir computing (RC), first applied to temporal signal processing, is a recurrent neural
network in which neurons are randomly connected. Once initialized, the connection …

Reservoir computing (RC) is a class of neuromorphic computing approaches that deals
particularly well with time-series prediction tasks. It significantly reduces the training …

As the 2020 roadblock approaches, the need of breakthrough in computing systems has
directed researchers to novel computing paradigms. The recently emerged reservoir …

In this paper, we utilize Negative Bias Temperature Instability (NBTI) effect in pFETs as a
computing mechanism. Specifically, NBTI is capable of implementing a physical reservoir …

The reservoir computing, an emerging computing paradigm, has proven its benefit to
multifarious applications. In this work, we successfully designed and fabricated an analog …

Following the computation revolution in the field of machine learning, the reservoir
computing system has shown its promising perspectives toward mimicking our mammalian …

Delay-coupled systems have recently made progress in the field of neuromorphic
computing, which can effectively process unprecedented amount of data at high speed. It is …