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

Memristive systems and devices are potentially available for implementing reservoir
computing (RC) systems applied to pattern recognition. However, the computational ability …

Memristor‐based physical reservoir computing (RC) is a robust framework for processing
complex spatiotemporal data parallelly. However, conventional memristor‐based reservoirs …

The massive growth in the Internet of Things (IoT) has led to an increase in demand for
devices receiving and transmitting data to and from the cloud during operations. Edge …

The booming development of artificial intelligence (AI) requires faster physical processing
units as well as more efficient algorithms. Recently, reservoir computing (RC) has emerged …

The ability to efficiently analyze the activities of biological neural networks can significantly
promote our understanding of neural communications and functionalities. However …

Reservoir computing (RC) is a framework that can extract features from a temporal input into
a higher‐dimension feature space. The reservoir is followed by a readout layer that can …

As feature-size scaling and" Moore's Law" in integrated CMOS circuits further slows down,
attention is shifting to computing by non-von Neumann and non-Boolean computing models …

Reservoir computing (RC), as a brain-inspired neuromorphic computing algorithm, is
capable of fast and energy-efficient temporal data analysis and prediction. Hardware …

Herein, a self-rectifying resistive switching memristor synapse with a Ta/NbO x/Pt structure
was demonstrated for deep reservoir computing (RC). The memristor demonstrated stable …