Bala, Anu ORCID: https://orcid.org/0009-0000-6242-5248, Adeyemo, Adedotun, Yang, Xiaohan and Jabir, Abusaleh (2018) A Memristive Activation Circuit for Deep Learning Neural Networks. In: 2018 8th International Symposium on Embedded Computing and System Design (ISED). IEEE

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Abstract

A highly efficient memristor MIN function based activation circuit is presented for memristive neuromorphic systems, using only two memristors and a comparator. The ReLU activation function is approximated using this circuit for the first time. The ReLU activation function helps to significantly reduce the time and computational cost of training in neuromorphic systems due to its simplicity and effectiveness in deep neural networks. A multilayer neural network is simulated using this activation circuit in addition to traditional memristor crossbar arrays. The results illustrate that the proposed circuit is able to perform training effectively with significant savings in time and area in memristor crossbar based neural networks.

Item Type:	Book Section
Status:	Published
DOI:	10.1109/ised.2018.8704116
Subjects:	T Technology > T Technology (General)
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/13539

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