Abstract
The source model discussed throughout this chapter is the Discrete Source (DS). Such a source is a pair \((\mathcal{X},P)\), where \(\mathcal{X}\triangleq \{1,\dots ,a\}\), say, is a finite alphabet and \(P\triangleq (P(1),\dots ,P(a))\) is a probability distribution on \(\mathcal{X}\). A discrete source can also be described by a random variable \(X:\mathcal{X}\rightarrow \mathcal{X}\), where \(\text {Prob}(X=x)=P(x)\) for all \(x\in \mathcal{X}\).
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Notes
- 1.
As for entropy-typical sequences we use analogous abbreviations for typical sequences in terms of \(n\), \(P\), and \(\delta \).
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Ahlswede, R., Ahlswede, A., Althöfer, I., Deppe, C., Tamm, U. (2014). Data Compression. In: Ahlswede, A., Althöfer, I., Deppe, C., Tamm, U. (eds) Storing and Transmitting Data. Foundations in Signal Processing, Communications and Networking, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-05479-7_2
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