Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Probing switching mechanism of memristor for neuromorphic computing
View through CrossRef
Abstract
In recent, neuromorphic computing has been proposed to simulate the human brain system to overcome bottlenecks of the von Neumann architecture. Memristors, considered emerging memory devices, can be used to simulate synapses and neurons, which are the key components of neuromorphic computing systems. To observe the resistive switching (RS) behavior microscopically and probe the local conductive filaments (CFs) of the memristors, conductive atomic force microscopy (CAFM) with the ultra-high resolution has been investigated, which could be helpful to understand the dynamic processes of synaptic plasticity and the firing of neurons. This review presents the basic working principle of CAFM and discusses the observation methods using CAFM. Based on this, CAFM reveals the internal mechanism of memristors, which is used to observe the switching behavior of memristors. We then summarize the synaptic and neuronal functions assisted by CAFM for neuromorphic computing. Finally, we provide insights into discussing the challenges of CAFM used in the neuromorphic computing system, benefiting the expansion of CAFM in studying neuromorphic computing-based devices.
Title: Probing switching mechanism of memristor for neuromorphic computing
Description:
Abstract
In recent, neuromorphic computing has been proposed to simulate the human brain system to overcome bottlenecks of the von Neumann architecture.
Memristors, considered emerging memory devices, can be used to simulate synapses and neurons, which are the key components of neuromorphic computing systems.
To observe the resistive switching (RS) behavior microscopically and probe the local conductive filaments (CFs) of the memristors, conductive atomic force microscopy (CAFM) with the ultra-high resolution has been investigated, which could be helpful to understand the dynamic processes of synaptic plasticity and the firing of neurons.
This review presents the basic working principle of CAFM and discusses the observation methods using CAFM.
Based on this, CAFM reveals the internal mechanism of memristors, which is used to observe the switching behavior of memristors.
We then summarize the synaptic and neuronal functions assisted by CAFM for neuromorphic computing.
Finally, we provide insights into discussing the challenges of CAFM used in the neuromorphic computing system, benefiting the expansion of CAFM in studying neuromorphic computing-based devices.
Related Results
Circuit modeling of memristors
Circuit modeling of memristors
Problem setting. Over the past few decades, the growth of electronic and computing power has fundamentally changed our work and life, and it is expected that significant new change...
A Memristor-Based Cascaded Neural Networks for Specific Target Recognition
A Memristor-Based Cascaded Neural Networks for Specific Target Recognition
Multiply-accumulate calculations using a memristor crossbar array is an important method to realize neuromorphic computing. However, the memristor array fabrication technology is s...
Robust analogue neuromorphic hardware networks using intrinsic physics-adaptive learning
Robust analogue neuromorphic hardware networks using intrinsic physics-adaptive learning
Abstract
Analogue neuromorphic computing hardware is highly energy-efficient and has been regarded as one of the most promising technologies for advancing artificial intell...
Memristor-based adaptive neuromorphic perception in unstructured environments
Memristor-based adaptive neuromorphic perception in unstructured environments
AbstractEfficient operation of control systems in robotics or autonomous driving targeting real-world navigation scenarios requires perception methods that allow them to understand...
Memristor Circuits for Simulating Neuron Spiking and Burst Phenomena
Memristor Circuits for Simulating Neuron Spiking and Burst Phenomena
Since the introduction of memristors, it has been widely recognized that they can be successfully employed as synapses in neuromorphic circuits. This paper focuses on showing that ...
Solution-Processed Small Molecule Memristors: From Nanowire Arrays to Thin-Films
Solution-Processed Small Molecule Memristors: From Nanowire Arrays to Thin-Films
Conventional computing architectures based on the Von Neumann model are nearing their physical and operational limitations, driven by the breakdown of Moore’s law, memory bottlenec...
Harnessing nonlinear conductive characteristic of TiO2/HfO2 memristor crossbar for implementing parallel vector–matrix multiplication
Harnessing nonlinear conductive characteristic of TiO2/HfO2 memristor crossbar for implementing parallel vector–matrix multiplication
Memristor crossbar arrays are expected to achieve highly energy-efficient neuromorphic computing via implementing parallel vector–matrix multiplication (VMM) in situ. The similarit...
Super‐Linear‐Threshold‐Switching Selector with Multiple Jar‐Shaped Cu‐Filaments in the Amorphous Ge3Se7 Resistive Switching Layer in a Cross‐Point Synaptic Memristor Array
Super‐Linear‐Threshold‐Switching Selector with Multiple Jar‐Shaped Cu‐Filaments in the Amorphous Ge3Se7 Resistive Switching Layer in a Cross‐Point Synaptic Memristor Array
AbstractThe learning and inference efficiencies of an artificial neural network represented by a cross‐point synaptic memristor array can be achieved using a selector, with high se...