Data-Dependent Statistical Memory Model for Passive Array of Memristive Devices

Author

Shin, Sangho ; Kim, Yungmin ; Kang, Sung-Mo

Author_Institution

Sch. of Eng., Univ. of California-Merced, Merced, CA, USA

Volume

57

Issue

12

fYear

2010

Firstpage

986

Lastpage

990

Abstract

A 2 × 2 equivalent statistical circuit model is presented to deal with sneak currents and random data distributions for n × m passive memory arrays of memristive devices. The data-dependent 2 × 2 circuit model enables a broad range of analysis, such as the optimum detection voltage margin, with computational efficiency and has no limit on the memory array size. In addition, we propose replica-based self-adaptable sense resistors to achieve both low-power reading and large voltage detection windowing.

Keywords

memristors; random-access storage; statistical analysis; computational efficiency; data-dependent statistical memory model; equivalent statistical circuit model; memristive device; optimum detection voltage margin; passive memory array; random data distribution; replica-based self-adaptable sense resistor; sneak current; voltage detection windowing; Approximation methods; Data models; Integrated circuit modeling; Mathematical model; Memristors; Nonvolatile memory; Data pattern dependence; memristive devices; nonvolatile resistive memory; statistical model;

fLanguage

English

Journal_Title

Circuits and Systems II: Express Briefs, IEEE Transactions on

Publisher

ieee

ISSN

1549-7747

Type

jour

DOI

10.1109/TCSII.2010.2083191

Filename

5610713