t,r;insrnit.. Depending on the presence or absence of ot.lier users, each user will be able to achieve different rates. In particular. certain bit,s n-ill be .received in the absence of other users but not in t,he presence of other users. Since some transniitted bits mill be lost owing to collisions. the capacit.y lve consider is maxiinurn rel iablyreceived rate rather than niasiiiium rel iably...

It is shown that nested polar codes achieve the Shannon capacity of arbitrary discrete memoryless sources and the Shannon capacity of arbitrary discrete memory less channels.

In general, Shannon zero-capacity is hard to obtain even for very simple small graphs. Lovasz constructed an upper bound in [4] for Shannon capacity which is well-characterized and relatively easy to compute. In some special cases, it is even equal to the Shannon capacity. However, it has been proven that the Lovasz bound is not always tight and counterexamples are not hard to find.

Integral imaging systems performance has been previously investigated with regard to different parameters such as lateral resolution, field of view, and depth of view. Those parameters are linked to one another, and, since the information capacity of an integral imaging system is finite, there are always trade-offs among them. We use the Shannon number and information capacity limit as figures ...

Shannon introduced the concept of zero-error capacity of a discrete memoryless channel. The channel determines an undirected graph on the symbol alphabet, where adjacency means that symbols cannot be confused at the receiver. The zero-error or Shannon capacity is an invariant of this graph. Gargano, Korner, and Vaccaro have recently extended the concept of Shannon capacity to directed graphs. T...

The index coding capacity is investigated through its structural properties. First, the capacity is characterized in three new multiletter expressions involving the clique number, Shannon capacity, and Lovász theta function of the confusion graph, the latter notion introduced by Alon, Hassidim, Lubetzky, Stav, and Weinstein. The main idea is that every confusion graph can be decomposed into a s...