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[HTML][HTML] Recent advances in physical reservoir computing: A review
Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …
processing. It is derived from several recurrent neural network models, including echo state …
Binary metal oxide-based resistive switching memory devices: a status review
Semiconductor memories are essential ingredients of modern electronic devices. Resistive
Random-Access Memories (RRAMs) have emerged as better alternatives for conventional …
Random-Access Memories (RRAMs) have emerged as better alternatives for conventional …
Artificial neural networks enabled by nanophotonics
The growing demands of brain science and artificial intelligence create an urgent need for
the development of artificial neural networks (ANNs) that can mimic the structural, functional …
the development of artificial neural networks (ANNs) that can mimic the structural, functional …
Access devices for 3D crosspoint memory
The emergence of new nonvolatile memory (NVM) technologies—such as phase change
memory, resistive, and spin-torque-transfer magnetic RAM—has been motivated by exciting …
memory, resistive, and spin-torque-transfer magnetic RAM—has been motivated by exciting …
[PDF][PDF] SPICE Model of Memristor with Nonlinear Dopant Drift.
A mathematical model of the prototype of memristor, manufactured in 2008 in Hewlett-
Packard Labs, is described in the paper. It is shown that the hitherto published approaches …
Packard Labs, is described in the paper. It is shown that the hitherto published approaches …
Ultralow energy consumption angstrom-fluidic memristor
The emergence of nanofluidic memristors has made a giant leap to mimic the neuromorphic
functions of biological neurons. Here, we report neuromorphic signaling using Angstrom …
functions of biological neurons. Here, we report neuromorphic signaling using Angstrom …
A discrete memristive neural network and its application for character recognition
Abstract Design of artificial neural networks based on memristor has attracted increasing
attentions from researchers. However, there are no reports on the discrete memristor based …
attentions from researchers. However, there are no reports on the discrete memristor based …
A versatile memristor model with nonlinear dopant kinetics
The need for reliable models that take into account the nonlinear kinetics of dopants is
nowadays of paramount importance, particularly with the physical dimensions of electron …
nowadays of paramount importance, particularly with the physical dimensions of electron …
Memristor-based cellular nonlinear/neural network: design, analysis, and applications
Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively
parallel architecture capable of solving complex engineering problems by performing …
parallel architecture capable of solving complex engineering problems by performing …
Adaptive oxide electronics: A review
Novel information processing techniques are being actively explored to overcome
fundamental limitations associated with CMOS scaling. A new paradigm of adaptive …
fundamental limitations associated with CMOS scaling. A new paradigm of adaptive …