Deriving the Probabilistic Capacity of General Run-Length Sets Using Generating Functions

Details Deriving the Probabilistic Capacity of General Run-Length Sets Using Generating Functions Deriving the Probabilistic Capacity of General Run-Length Sets Using Generating Functions

2010-01-13

arxiv.org/abs/1001.2205v1

Computer Science

Information Theory

5 pages, submitted to ISIT 2010

Scientific paper

In "Reliable Communication in the Absence of a Common Clock" (Yeung et al., 2009), the authors introduce general run-length sets, which form a class of constrained systems that permit run-lengths from a countably infinite set. For a particular definition of probabilistic capacity, they show that probabilistic capacity is equal to combinatorial capacity. In the present work, it is shown that the same result also holds for Shannon's original definition of probabilistic capacity. The derivation presented here is based on generating functions of constrained systems as developed in "On the Capacity of Constrained Systems" (Boecherer et al., 2010) and provides a unified information-theoretic treatment of general run-length sets.

Affiliated with

Also associated with

No associations

Rating

Deriving the Probabilistic Capacity of General Run-Length Sets Using Generating Functions 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 Deriving the Probabilistic Capacity of General Run-Length Sets Using Generating Functions, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Deriving the Probabilistic Capacity of General Run-Length Sets Using Generating Functions will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-525703