Universal Lossless Data Compression Via Binary Decision Diagrams

Details Universal Lossless Data Compression Via Binary Decision Diagrams Universal Lossless Data Compression Via Binary Decision Diagrams

2011-11-06

arxiv.org/abs/1111.1432v1

Computer Science

Information Theory

Scientific paper

A binary string of length $2^k$ induces the Boolean function of $k$ variables whose Shannon expansion is the given binary string. This Boolean function then is representable via a unique reduced ordered binary decision diagram (ROBDD). The given binary string is fully recoverable from this ROBDD. We exhibit a lossless data compression algorithm in which a binary string of length a power of two is compressed via compression of the ROBDD associated to it as described above. We show that when binary strings of length $n$ a power of two are compressed via this algorithm, the maximal pointwise redundancy/sample with respect to any s-state binary information source has the upper bound $(4\log_2s+16+o(1))/\log_2n $. To establish this result, we exploit a result of Liaw and Lin stating that the ROBDD representation of a Boolean function of $k$ variables contains a number of vertices on the order of $(2+o(1))2^{k}/k$.

Affiliated with

Also associated with

No associations

Rating

Universal Lossless Data Compression Via Binary Decision Diagrams 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 Universal Lossless Data Compression Via Binary Decision Diagrams, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Universal Lossless Data Compression Via Binary Decision Diagrams will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-704786