Memristor networks for real-time neural activity analysis

Designing energy efficient artificial neural networks for real-time analysis remains a challenge. Here, the authors report the development of a perovskite halide (CsPbI3) memristor-based Reservoir Computing system for real-time recognition of neural firing patterns and neural synchronization states.

Bibliographic Details
Main Authors: Xiaojian Zhu, Qiwen Wang, Wei D. Lu
Format: Article
Language:English
Published: Nature Publishing Group 2020-05-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-020-16261-1
Description
Summary:Designing energy efficient artificial neural networks for real-time analysis remains a challenge. Here, the authors report the development of a perovskite halide (CsPbI3) memristor-based Reservoir Computing system for real-time recognition of neural firing patterns and neural synchronization states.
ISSN:2041-1723