Publication
IEEE TNANO
Paper

Wave-based neuromorphic computing framework for brain-like energy efficiency and integration

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Abstract

We present a framework of wave-based neuromorphic computing aiming at brain-like capabilities and efficiencies with nanoscale device integration. We take advantage of the unique nature of elastic nondissipative wave dynamics in both computations and IO communications in between as a means to natively implement and execute neuromorphic computing functions such as weighted sum in a spatiotemporal manner. Lower bound analysis based on a memory model and wave group velocity scaling is provided for conceptual evaluations.

Date

01 Sep 2016

Publication

IEEE TNANO

Authors

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