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Number Systems for Deep Neural Network Architectures

Name: Number Systems for Deep Neural Network Architectures
Brand: Springer, Berlin
SKU: 43654697
Price: 51.09 EUR
Availability: InStock
Author: Ghada Alsuhli
ISBN: 9783031381324

Language

English

Book Hardback

Libristo code: 43654697

Publishers Springer, Berlin, November 2022

This book provides readers a comprehensive introduction to alternative number systems for more effic... Full description

Libristo code: 43654697

125 b

51.09 € VAT included

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This book provides readers a comprehensive introduction to alternative number systems for more efficient representations of Deep Neural Network (DNN) data. Various number systems (conventional/unconventional) exploited for DNNs are discussed, including Floating Point (FP), Fixed Point (FXP), Logarithmic Number System (LNS), Residue Number System (RNS), Block Floating Point Number System (BFP), Dynamic Fixed-Point Number System (DFXP) and Posit Number System (PNS). The authors explore the impact of these number systems on the performance and hardware design of DNNs, highlighting the challenges associated with each number system and various solutions that are proposed for addressing them.