Computer Science – Information Theory
Scientific paper
2010-10-07
Computer Science
Information Theory
Scientific paper
Let $\mathcal{X}$ and $\mathcal{Y}$ be finite alphabets and $P_{XY}$ a joint distribution over them, with $P_X$ and $P_Y$ representing the marginals. For any $\epsilon > 0$, the set of $n$-length sequences $x^n$ and $y^n$ that are jointly typical \cite{ckbook} according to $P_{XY}$ can be represented on a bipartite graph. We present a formal definition of such a graph, known as a \emph{typicality} graph, and study some of its properties.
Anastasopoulos Achilleas
Krithivasan Dinesh
Nazari Ali
Pradhan Sandeep S.
Venkataramanan Ramji
No associations
LandOfFree
Typicality Graphs:Large Deviation Analysis does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Typicality Graphs:Large Deviation Analysis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Typicality Graphs:Large Deviation Analysis will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-508740