TY - CHAP
T1 - A Simpler Analysis of Burrows-Wheeler Based Compression.
AU - Lewenstein, Moshe
AU - Valiente, Gabriel
AU - Kaplan, Haim
AU - Landau, Shir
AU - Verbin, Elad
PY - 2006
Y1 - 2006
N2 - In this paper we present a new technique for worst-case analysis of compression algorithms which are based on the Burrows-Wheeler Transform. We deal mainly with the algorithm purposed by Burrows and Wheeler in their first paper on the subject [6], called bw0. This algorithm consists of the following three steps: 1) Compute the Burrows-Wheeler transform of the text, 2) Convert the transform into a sequence of integers using the move-to-front algorithm, 3) Encode the integers using Arithmetic code or any order-0 encoding (possibly with run-length encoding). We prove a strong upper bound on the worst-case compression ratio of this algorithm. This bound is significantly better than bounds known to date and is obtained via simple analytical techniques. Specifically, we show that for any input string s, and μ> 1, the length of the compressed string is bounded by μ·s Hk(s) + log(ζ(μ)) ·s + gk where Hk is the k-th order empirical entropy, gk is a consta
AB - In this paper we present a new technique for worst-case analysis of compression algorithms which are based on the Burrows-Wheeler Transform. We deal mainly with the algorithm purposed by Burrows and Wheeler in their first paper on the subject [6], called bw0. This algorithm consists of the following three steps: 1) Compute the Burrows-Wheeler transform of the text, 2) Convert the transform into a sequence of integers using the move-to-front algorithm, 3) Encode the integers using Arithmetic code or any order-0 encoding (possibly with run-length encoding). We prove a strong upper bound on the worst-case compression ratio of this algorithm. This bound is significantly better than bounds known to date and is obtained via simple analytical techniques. Specifically, we show that for any input string s, and μ> 1, the length of the compressed string is bounded by μ·s Hk(s) + log(ζ(μ)) ·s + gk where Hk is the k-th order empirical entropy, gk is a consta
U2 - 10.1007/11780441_26
DO - 10.1007/11780441_26
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SN - 9783540354550
SP - 282
EP - 293
BT - Combinatorial Pattern Matching
ER -