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As a consequence of the structure of y, it is easy to see that it can be compressed with the following redundancy,

r | T | ( r - 1 ) 2 log ( n | T | + O ( 1 ) ) + | T | log ( n ) ,

where the new | T | log ( n ) term arises from coding the locations of transitions between segments (states of the tree) in the BWT output. Not only is the BWT convenient for compression, but it is amenable to fast computation. Both the BWT and its inverse can be implemented in O ( n ) time. This combination of great compression and speed has made the BWT quite popular in compressors that have appeared since the late 1990s. For example, the bzip2 archiving package is very popular among network administrators.

That said, from a theoretical perspective the BWT suffers from an extraneous redundancy of | T | log ( n ) bits. Until this gap was resolved, the theoretical community still preferred the semi-predictive method or another approach based on mixtures.

Semi-predictive coding using the bwt

Another approach for using the BWT is to use y only for learning the MDL tree source T * . To do so, note that when the BWT is run, it is possible to track the correspondences between contexts and segments of the BWT output. Therefore, information about per-segment symbol count is available, and can be easily applied to perform the tree pruning procedure that we have seen. Not only that, but some BWT computation algorithms (e.g., suffix tree approaches) maintain this information for all context depths and not just bounded D . In short, the BWT allows to compute the minimizing tree T * in linear time  [link] .

Given the minimizing tree T * , it is not obvious how to determine which state generated each character of y (respectively, x ) in linear time. It has been shown by Martín et al.  [link] that this step can also be performed in linear time by developing a state machine whose states include the leaves of T * . The result is a two part code, where the first part computes the optimal T * via BWT, and the second part actually compresses x by tracking which state of T * generated each of the symbols. To summarize, we have a linear complexity algorithm for compressing and decompressing a source while achieving the redundancy bounds for the class of tree sources.

Context tree weighting

We discussed in [link] for the problem of encoding a transition between two known i.i.d. distributions that

1 n i = 1 n p θ i ( x ) > 1 n max i { p θ i ( x ) } .

Therefore, a mixture over all parameter values yields a greater probability (and thus lower coding length) than the maximizing approach. Keep in mind that finding the optimal MDL tree source T * is analogous to the plug-in approach, and it would reduce the coding length if we could assign the probability as a mixture over all possible trees, where we assign trees with fewer leaves a greater weight. That is, ideally we want to implement

Pr ( x ) = T 2 - | code ( T ) | · p T ( x ) ,

where | code ( T ) | is the length of the encoding procedure that we discussed for the tree structure T , and p T ( x ) is the probability for the sequence x under the model T .

Willems et al. showed how to implement such a mixture in a simple way over the class of tree sources of bounded depth D . As before, the algorithm proceeds in a bottom up manner from leaves toward the root. At leaves, the probability p s assigned to symbols that were generated within that context s is the Krichevsky-Trofimov probability, p K T ( s , x )   [link] . For s that is an internal node whose depth is less than D , the approach by Willems et al.  [link] is to mix ( i ) the probabilities of keeping the branches for 0s and 1s and ( ii ) pruning,

p s = 1 2 p K T ( s , x ) + 1 2 p 0 s · p 1 s .

It can be shown that this simple formula allows to implement a mixture over the class of bounded depth context tree sources, thus reducing the coding length w.r.t. the semi-predictive approach.

In fact, Willems later showed how to extend the context tree weighting (CTW) approach to tree sources of unbounded depth  [link] . Unfortunately, while the basic bounded depth CTW has complexity that is comparable to the BWT, the unboundedCTW has potentially higher complexity.

Questions & Answers

how can chip be made from sand
Eke Reply
is this allso about nanoscale material
are nano particles real
Missy Reply
Hello, if I study Physics teacher in bachelor, can I study Nanotechnology in master?
Lale Reply
no can't
where is the latest information on a no technology how can I find it
where we get a research paper on Nano chemistry....?
Maira Reply
nanopartical of organic/inorganic / physical chemistry , pdf / thesis / review
what are the products of Nano chemistry?
Maira Reply
There are lots of products of nano chemistry... Like nano coatings.....carbon fiber.. And lots of others..
Even nanotechnology is pretty much all about chemistry... Its the chemistry on quantum or atomic level
no nanotechnology is also a part of physics and maths it requires angle formulas and some pressure regarding concepts
Preparation and Applications of Nanomaterial for Drug Delivery
Hafiz Reply
Application of nanotechnology in medicine
has a lot of application modern world
what is variations in raman spectra for nanomaterials
Jyoti Reply
ya I also want to know the raman spectra
I only see partial conversation and what's the question here!
Crow Reply
what about nanotechnology for water purification
RAW Reply
please someone correct me if I'm wrong but I think one can use nanoparticles, specially silver nanoparticles for water treatment.
yes that's correct
I think
Nasa has use it in the 60's, copper as water purification in the moon travel.
nanocopper obvius
what is the stm
Brian Reply
is there industrial application of fullrenes. What is the method to prepare fullrene on large scale.?
industrial application...? mmm I think on the medical side as drug carrier, but you should go deeper on your research, I may be wrong
How we are making nano material?
what is a peer
What is meant by 'nano scale'?
What is STMs full form?
scanning tunneling microscope
how nano science is used for hydrophobicity
Do u think that Graphene and Fullrene fiber can be used to make Air Plane body structure the lightest and strongest. Rafiq
what is differents between GO and RGO?
what is simplest way to understand the applications of nano robots used to detect the cancer affected cell of human body.? How this robot is carried to required site of body cell.? what will be the carrier material and how can be detected that correct delivery of drug is done Rafiq
analytical skills graphene is prepared to kill any type viruses .
Any one who tell me about Preparation and application of Nanomaterial for drug Delivery
what is Nano technology ?
Bob Reply
write examples of Nano molecule?
The nanotechnology is as new science, to scale nanometric
nanotechnology is the study, desing, synthesis, manipulation and application of materials and functional systems through control of matter at nanoscale
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Source:  OpenStax, Universal algorithms in signal processing and communications. OpenStax CNX. May 16, 2013 Download for free at http://cnx.org/content/col11524/1.1
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