Number Systems for Deep Neural Network Architectures is popular PDF and ePub book, written by Ghada Alsuhli in 2023-09-01, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Number Systems for Deep Neural Network Architectures can be Read Online from any device for your convenience.
Number Systems for Deep Neural Network Architectures Book PDF Summary
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.
Detail Book of Number Systems for Deep Neural Network Architectures PDF
- Author : Ghada Alsuhli
- Release : 01 September 2023
- Publisher : Springer Nature
- ISBN : 9783031381331
- Genre : Technology & Engineering
- Total Page : 100 pages
- Language : English
- PDF File Size : 13,6 Mb
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