Advances in Memristors, Memristive Devices and Systems
A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "E：Engineering and Technology".
Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 3802
Special Issue Editor
Special Issue Information
Dear Colleagues,
With the recent advances in artificial intelligence (AI) technology, memristor devices and systems have received significant interest as a building block for deep neural network and spiking neural network. A two-terminal memristor device has been developed for highly scalable and low-energy consuming electronic synapse and neuron devices. The functions of biological synapses and neurons can easily be emulated using the memristor device, including long and short-term potentiation/depression, spike-timing dependent plasticity, and leaky integrate-and fire. Using these unique features of memristor, the memristor system has successfully demonstrated various neural networks such as deep neural network, convolutional neural network, recurrent neural network, reinforcement learning, and spiking neural network. These demonstrations increase researchers’ access to memristor devices and systems and speed up the development of hardware-based in memory computing for energy-efficient AI technology. Therefore, the goal of this Special Issue is to present research papers and review articles that focus on novel device engineering in memristors and its use for various neural network applications.
Dr. Byung Chul Jang
Guest Editor
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Keywords
- memristor
- memristive system
- neuromorphic computing
- nonvolatile logic-in-memory circuit
- in-memory computing
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