Fast Approximations of Activation Functions in Deep Neural Networks when using Posit Arithmetic

Fast Approximations of Activation Functions in Deep Neural Networks when using Posit Arithmetic

With increasing real-time constraints being put on the use of Deep Neural Networks (DNNs) by real-time scenarios, there is the need to review information representation. A very challenging path is to employ an encoding that allows a fast processing and hardware-friendly representation of information...

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Bibliographic Details
Main Authors: Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Sensors
Subjects:
alternative representations to float numbers
posit arithmetic
deep neural networks (dnns)
neural network activation functions
Online Access:https://www.mdpi.com/1424-8220/20/5/1515

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https://www.mdpi.com/1424-8220/20/5/1515

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