Wave physics as an analog recurrent neural network

Friday, January 10, 2020 - 09:40 in Physics & Chemistry

Analog machine learning hardware offers a promising alternative to digital counterparts as a more energy efficient and faster platform. Wave physics based on acoustics and optics is a natural candidate to build analog processors for time-varying signals. In a new report on Science AdvancesTyler W. Hughes and a research team in the departments of Applied Physics and Electrical Engineering at Stanford University, California, identified mapping between the dynamics of wave physics and computation in recurrent neural networks.

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