Bon Woong Ku, Catherine D. Schuman, Md Musabbir Adnan, Tiffany M. Mintz, Raphael Pooser, Kathleen E. Hamilton, Garrett S. Rose and Sung Kyu Lim

March, 2022

ACM Journal on Emerging Technologies in Computer Systems (JETC)

https://doi.org/10.1145/3473036

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Abstract

This work addresses how to naturally adopt the l2-norm cosine similarity in the neuromemristive system and studies the unsupervised learning performance on handwritten digit image recognition. Proposed architecture is a two-layer fully connected neural network with a hard winner-take-all (WTA) learning module. For input layer, we propose single-spike temporal code that transforms input stimuli into the set of single spikes with different latencies and voltage levels. For a synapse model, we employ a compound memristor where stochastically switching binary-state memristors connected in parallel, which offers a reliable and scalable multi-state solution for synaptic weight storage. Hardware-friendly synaptic adaptation mechanism is proposed to realize spike-timing-dependent plasticity learning. Input spikes are sent out through those memristive synapses to each and every integrate-and-fire neuron in the fully connected output layer, where the hard WTA network motif introduces the competition based on cosine similarity for the given input stimuli. Finally, we present 92.64% accuracy performance on unsupervised digit recognition with only single-epoch MNIST dataset training via high-level simulations, including extensive analysis on the impact of system parameters.

Citation Information

Text

author    B. W. Ku and C. D. Schuman and M. M. Adnan and T. M. Mintz and
          R. Pooser and K. E. Hamilton and G. S. Rose and S. K. Lim
title     Unsupervised Digit Recognition Using Cosine Similarity In A 
          Neuromemristive Competitive Learning System
journal   ACM Journal on Emerging Technologies in Computer Systems (JETC)
volume    18
number    2
pages     1-20
year      2022
url       https://doi.org/10.1145/3473036
doi       10.1145/3473036

Bibtex

@ARTICLE{ksa:22:udr,
    author = "B. W. Ku and C. D. Schuman and M. M. Adnan and T. M. Mintz and
                R. Pooser and K. E. Hamilton and G. S. Rose and S. K. Lim",
    title = "Unsupervised Digit Recognition Using Cosine Similarity In A 
                Neuromemristive Competitive Learning System",
    journal = "ACM Journal on Emerging Technologies in Computer Systems (JETC)",
    volume = "18",
    number = "2",
    pages = "1-20",
    year = "2022",
    url = "https://doi.org/10.1145/3473036",
    doi = "10.1145/3473036"
}