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4 October 2022 Binarized neuromorphic inference network with STT MTJ synapses (Conference Presentation)
Peng Zhou, Alexander J. Edwards, Fred B. Mancoff, Dimitri Houssameddine, Sanjeev Aggarwal, Joseph S. Friedman
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Proceedings Volume PC12205, Spintronics XV; PC122050O (2022) https://doi.org/10.1117/12.2633571
Event: SPIE Nanoscience + Engineering, 2022, San Diego, California, United States
Abstract
We present the first experimental demonstration of a neuromorphic network with magnetic tunnel junction (MTJ) synapses, which performs image recognition via vector-matrix multiplication. We also simulate a large MTJ network performing MNIST handwritten digit recognition, demonstrating that MTJ crossbars can match memristor accuracy while providing increased precision, stability, and endurance.
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Peng Zhou, Alexander J. Edwards, Fred B. Mancoff, Dimitri Houssameddine, Sanjeev Aggarwal, and Joseph S. Friedman "Binarized neuromorphic inference network with STT MTJ synapses (Conference Presentation)", Proc. SPIE PC12205, Spintronics XV, PC122050O (4 October 2022); https://doi.org/10.1117/12.2633571
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KEYWORDS
Analog electronics
Binary data
Stochastic processes
Magnetism
Neural networks
Neurons
Oscillators
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