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Title: Diffusive Memristors with Uniform and Tunable Relaxation Time for Spike Generation in Event‐Based Pattern Recognition
Abstract

A diffusive memristor is a promising building block for brain‐inspired computing hardware. However, the randomness in the device relaxation dynamics limits the wide‐range adoption of diffusive memristors in large arrays. In this work, the device stack is engineered to achieve a much‐improved uniformity in the relaxation time (standard deviation σ reduced from ≈12 to ≈0.32 ms). The memristor is further connected with a resistor or a capacitor and the relaxation time is tuned between 1.13 µs and 1.25 ms, ranging from three orders of magnitude. The hierarchy of time surfaces (HOTS) algorithm, to utilize the tunable and uniform relaxation behavior for spike generation, is implemented. An accuracy of 77.3% is achieved in recognizing moving objects in the neuromorphic MNIST (N‐MNIST) dataset. The work paves the way for building emerging neuromorphic computing hardware systems with ultralow power consumption.

 
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Award ID(s):
2023752
NSF-PAR ID:
10373233
Author(s) / Creator(s):
 ;  ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Advanced Materials
ISSN:
0935-9648
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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    Acknowledgement

    This work was supported by the U.S. National Science Foundation (NSF) Award No. ECCS-1931088. S.L. and H.W.S. acknowledge the support from the Improvement of Measurement Standards and Technology for Mechanical Metrology (Grant No. 22011044) by KRISS.

    References

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