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Artificial Synapses for Neuromorphic Computing

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Tested against a dataset of handwritten images from the Modified National Standards and Technology database, the interface-type memristors realized a high image recognition accuracy of 94.72%.

Credit: Los Alamos National Laboratory

Los Alamos National Laboratory (LANL) researchers have developed an interface-type memristive device that could be used to create artificial synapses for next-generation neuromorphic computing.

Memristors can replicate the structure and function of synapses, the human brain's "in-memory processing" system; they also save time and energy by co-locating information storage and processing.

Comprised of a simple structure of gold and other semiconducting materials, the interface-type memristor could be scaled down to nanometer size and needs much less processing power than transistor-based neuromorphic chips.

LANL's Aiping Chen said the advantages of the new device include low-energy consumption, high parallelism, and excellent error tolerance, which ”make it very good for advanced computing tasks like learning, recognition, and decision-making."

From Los Alamos National Laboratory
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Abstracts Copyright © 2023 SmithBucklin, Washington, DC, USA


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