Title :
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
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;
Journal_Title :
Circuits and Systems II: Express Briefs, IEEE Transactions on
DOI :
10.1109/TCSII.2010.2083191
