Memristor devices have the potential to drive a new class of specialized low power embedded hardware. The unique characteristics of these non-volatile and nanoscale devices allow them to perform parallel analog computing with extreme efficiency. To help facilitate the design of such systems, this paper describes the fabrication and characterization process used to develop memristors that are strong candidates for use in neuromorphic systems. In this work two different types of memristor devices, those with a GeTe switching layer, and those with a VO2 switching layer, are characterized and analyzed. These results are used to determine device suitability for use in neuromorphic computing applications through the properties of symmetry, reliability, stability, and programmability. In short, repeatable multi-level resistive switching has been investigated and the results have been summarized.


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    Title :

    Experimental Study of Memristors for use in Neuromorphic Computing


    Contributors:


    Publication date :

    2018-07-01


    Size :

    870385 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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