Physical reservoir computing is a form of neuromorphic computing that harvests the dynamic
properties of materials for high-efficiency computing. A wide range of physical systems can …

In the reservoir computing literature, the information processing capacity is frequently used
to characterize the computing capabilities of a reservoir. However, it remains unclear how …

Physical reservoir computing is a framework that enables energy‐efficient information
processing by using physical systems. Nonlinear dynamics in physical systems provide a …

Abstract Quantum Reservoir Computing (QRC) offers potential advantages over classical
reservoir computing, including inherent processing of quantum inputs and a vast Hilbert …

Highlights•Neurodevelopment provides an opportunity to study emerging human
consciousness.•In/ex-ternal neuroelectric fields (NEF) form a feedback loop in neural …

Physical-reservoir computing (PRC) is an information-processing framework where the
nonlinear physics of a reservoir can be leveraged to compute a task. Since the readout …

Speech recognition is a critical task in the field of artificial intelligence (AI) and has
witnessed remarkable advancements thanks to large and complex neural networks, whose …

This paper investigates in detail the effects of measurement noise on the performance of
reservoir computing. We focus on an application in which reservoir computers are used to …

The main motivation of this paper is to introduce the ordinal diversity, a symbolic tool able to
quantify the degree of diversity of multiple time series. Analytical, numerical, and …

The process of training an artificial neural network involves iteratively adapting its
parameters so as to minimize the error of the network's prediction, when confronted with a …