Memristive devices for computing
Memristive devices are electrical resistance switches that can retain a state of internal
resistance based on the history of applied voltage and current. These devices can store and …
resistance based on the history of applied voltage and current. These devices can store and …
Redox-Based Resistive Switching Memories-Nanoionic Mechanisms, Prospects, and Challenges.
This review article introduces resistive switching processes that are being considered for
nanoelectronic nonvolatile memories. The three main classes are based on an …
nanoelectronic nonvolatile memories. The three main classes are based on an …
[HTML][HTML] Brain-inspired computing with memristors: Challenges in devices, circuits, and systems
This article provides a review of current development and challenges in brain-inspired
computing with memristors. We review the mechanisms of various memristive devices that …
computing with memristors. We review the mechanisms of various memristive devices that …
Power-efficient neural network with artificial dendrites
In the nervous system, dendrites, branches of neurons that transmit signals between
synapses and soma, play a critical role in processing functions, such as nonlinear …
synapses and soma, play a critical role in processing functions, such as nonlinear …
Li-ion synaptic transistor for low power analog computing
Nonvolatile redox transistors (NVRTs) based upon Li-ion battery materials are demonstrated
as memory elements for neuromorphic computer architectures with multi-level analog …
as memory elements for neuromorphic computer architectures with multi-level analog …
TEAM: Threshold adaptive memristor model
Memristive devices are novel devices, which can be used in applications ranging from
memory and logic to neuromorphic systems. A memristive device offers several advantages …
memory and logic to neuromorphic systems. A memristive device offers several advantages …
Nanosecond protonic programmable resistors for analog deep learning
Nanoscale ionic programmable resistors for analog deep learning are 1000 times smaller
than biological cells, but it is not yet clear how much faster they can be relative to neurons …
than biological cells, but it is not yet clear how much faster they can be relative to neurons …
Pattern classification by memristive crossbar circuits using ex situ and in situ training
Memristors are memory resistors that promise the efficient implementation of synaptic
weights in artificial neural networks. Whereas demonstrations of the synaptic operation of …
weights in artificial neural networks. Whereas demonstrations of the synaptic operation of …
Magneto-ionic control of interfacial magnetism
In metal/oxide heterostructures, rich chemical,, electronic,,, magnetic,,, and mechanical,
properties can emerge from interfacial chemistry and structure. The possibility to dynamically …
properties can emerge from interfacial chemistry and structure. The possibility to dynamically …
[HTML][HTML] Resistive switching phenomena: A review of statistical physics approaches
Resistive switching (RS) phenomena are reversible changes in the metastable resistance
state induced by external electric fields. After discovery∼ 50 years ago, RS phenomena …
state induced by external electric fields. After discovery∼ 50 years ago, RS phenomena …