Memristor’s characteristics: From non-ideal to ideal

Memristor has been widely studied in the field of neuromorphic computing and is considered to be a strong candidate to break the von Neumann bottleneck. However, the non-ideal characteristics of memristor seriously limit its practical application. There are two sides to everything, and memristors ar...

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Bibliographic Details
Published inChinese physics B Vol. 32; no. 2; pp. 28401 - 581
Main Authors Sun, Fan, Su, Jing, Li, Jie, Duan, Shukai, Hu, Xiaofang
Format Journal Article
LanguageEnglish
Published Chinese Physical Society and IOP Publishing Ltd 01.01.2023
College of Artificial Intelligence,Southwest University,Chongqing 400715,China
Subjects
genetic algorithm
memristor
non-ideal characteristic
path planning
genetic algorithm
non-ideal characteristic
path planning
memristor
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Summary:Memristor has been widely studied in the field of neuromorphic computing and is considered to be a strong candidate to break the von Neumann bottleneck. However, the non-ideal characteristics of memristor seriously limit its practical application. There are two sides to everything, and memristors are no exception. The non-ideal characteristics of memristors may become ideal in some applications. Genetic algorithm (GA) is a method to search for the optimal solution by simulating the process of biological evolution. It is widely used in the fields of machine learning, combinatorial optimization, and signal processing. In this paper, we simulate the biological evolutionary behavior in GA by using the non-ideal characteristics of memristors, based on which we design peripheral circuits and path planning algorithms based on memristor networks. The experimental results show that the non-ideal characteristics of memristor can well simulate the biological evolution behavior in GA.
ISSN:1674-1056
DOI:10.1088/1674-1056/ac7548