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Video s3
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    Presenter(s)
    Saveri Ricci Headshot
    Display Name
    Saveri Ricci
    Affiliation
    Affiliation
    Politecnico di Milano
    Country
    Author(s)
    Display Name
    Saveri Ricci
    Affiliation
    Affiliation
    Politecnico di Milano
    Display Name
    David Kappel
    Affiliation
    Affiliation
    University of Göttingen
    Affiliation
    Affiliation
    University of Göttingen
    Display Name
    Daniele Ielmini
    Affiliation
    Affiliation
    Politecnico di Milano
    Display Name
    Erika Covi
    Affiliation
    Affiliation
    NaMLab, Dresden, Germany
    Abstract

    The necessity of having an electronic device working in relevant biological time scales with a small footprint boosted the research of a new class of emerging memories. Ag-based volatile resistive switching memories (RRAMs) feature a spontaneous change of device conductance with a similarity to biological mechanisms. They rely on the formation and self-disruption of a metallic conductive filament through an oxide layer, with a retention time ranging from a few milliseconds to several seconds, greatly tunable according to the maximum current which is flowing through the device. Here we prove a neuromorphic system based on volatile-RRAMs able to mimic the principles of biological decision-making behavior and tackle the Two-Alternative Forced Choice problem, where a subject is asked to make a choice between two possible alternatives not relying on a precise knowledge of the problem, rather on noisy perceptions

    Slides
    • Decision Making by a Neuromorphic Network of Volatile Resistive Switching Memories (application/pdf)