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Analog backpropagation learning circuits for memristive crossbar neural networks

1 min read · Thu, Apr 26 2018

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Circuits tsmc CMOS

Krestinskaya, Olga, "Analog backpropagation learning circuits for memristive crossbar neural networks." 2018 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2018, 1. The implementation of backpropagation algorithm using gradient descent operation with analog circuits is an open problem. In this paper, we present the analog learning circuits for realizing backpropagation algorithm for use with neural networks in memristive crossbar arrays. The circuits are simulated in SPICE using TSMC 180nm CMOS process models, and HP memristor models. The gradient descent operations are

Flow Simulation at the Exascale (Exaflow)

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