Programmable Fading Memory in Atomic Switch Systems for Error Checking Applications
2021
Disruptive technology in computational devices is required as the universal computing machines approach quantum mechanical limits. Integration of state-of-the-art memristive devices provides optimal scaling of current technologies beyond this limit through the adoption of neuromorphic models. Universal computing machines pioneered by Alan Turing are strictly based on top-down intelligent design. Neuromorphic models instead engage in bottom-up programmability by emulating mammalian brain design and characteristics. Here we show the design, characterization, and implementation of a massively parallel memristor neuromorphic network based on metal chalcogenide atomic switch network (ASN) systems with key characteristics such as short- and long-term potentiation, power-law dynamics, and scale-free topology.
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