Title :
The state of the art of memristive neural systems: Models and applications
Author :
Ailong Wu ; Zhigang Zeng ; Chaojin Fu
Author_Institution :
Coll. of Math. & Stat., Hubei Normal Univ., Huangshi, China
Abstract :
Memristive neural systems are a groundbreaking concept that is helping to understand the behavior of many physical, technical and bionic systems. This paper reviews the research status of memristive neural systems in the past few years. Considering there are too many publications about the memristive neural systems, we summarize the relevant models and applications rather than contemplating to go into details of particular results. First, some representative models of memristive neural systems are simply introduced. Then, we briefly describe some novel applications in the related fields (dynamic information storage or retrieval, logical operations and ultra-high-performance computing). Subsequently, some existing problems are summarized, and finally, the trend of memristive neural systems is pointed out.
Keywords :
memristors; neural chips; dynamic information retrieval; dynamic information storage; logical operations; memristive neural systems; ultra-high-performance computing; Automata; Biological neural networks; Chaos; Computer architecture; Educational institutions; Memristors; Neuromorphics;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889375