Programmable Energy-Efficient Analog Multilayer Perceptron Architecture Suitable for Future Expansion to Hardware Accelerators

Programmable Energy-Efficient Analog Multilayer Perceptron Architecture Suitable for Future Expansion to Hardware Accelerators

A programmable, energy-efficient analog hardware implementation of a multilayer perceptron (MLP) is presented featuring a highly programmable system that offers the user the capability to create an MLP neural network hardware design within the available framework. In addition to programmability, thi...

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Bibliographic Details
Main Authors: Jeff Dix, Jeremy Holleman, Benjamin J. Blalock
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Journal of Low Power Electronics and Applications
Subjects:
neural network
multilayer perceptron
energy efficient
analog
weak inversion
programmable
Online Access:https://www.mdpi.com/2079-9268/13/3/47

Internet

https://www.mdpi.com/2079-9268/13/3/47

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