Summary
Binary coding provides yet another example of how entropy may be used to quantify the “complexity” of things. After reviewing the basics of binary coding, we present the fundamental inequalities of Kraft and McMillan, and then in Theorem 8.9 we present the entropic bound for the length of uniquely decipherable codes. We only touch upon the aspects of coding that have to do with entropy; a more comprehensive presentation of coding theory may be found, for instance, in [24].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Collet, JF. (2018). Application: binary coding. In: Discrete Stochastic Processes and Applications. Universitext. Springer, Cham. https://doi.org/10.1007/978-3-319-74018-8_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-74018-8_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-74017-1
Online ISBN: 978-3-319-74018-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)