Petrification vs Compression - What's the difference?
petrification | compression |
the process of replacing the organic residues of plants (and animals) with insoluble salts, the original shape and topography being retained
(figurative) obduracy; callousness
an increase in density; the act of compressing, or the state of being compressed; compaction
the cycle of an internal combustion engine during which the fuel and air mixture is compressed
(computing) the process by which data is compressed
* {{quote-web
, year = 2011
, author = Marcelo A. Montemurro & Damián H. Zanette
, title = Universal Entropy of Word Ordering Across Linguistic Families
, site = PLoS ONE
, url = http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0019875
, accessdate = 2012-09-26}}
(music) the electronic process by which any sound's gain is automatically controlled
(astronomy) the deviation of a heavenly body from a spherical form
As nouns the difference between petrification and compression
is that petrification is the process of replacing the organic residues of plants (and animals) with insoluble salts, the original shape and topography being retained while compression is an increase in density; the act of compressing, or the state of being compressed; compaction.petrification
English
(wikipedia petrification)Noun
- (Hallywell)
Synonyms
* petrifactioncompression
English
Noun
(en noun)- Due to the presence of long-range correlations in language [21], [22] it is not possible to compute accurate measures of the entropy by estimating block probabilities directly. More efficient nonparametric methods that work even in the presence of long-range correlations are based on the property that the entropy of a sequence is a lower bound to any lossless compressed version of it [15]. Thus, in principle, it is possible to estimate the entropy of a sequence by finding its length after being compressed by an optimal algorithm. In our analysis, we used an efficient entropy estimator derived from the Lempel-Ziv compression algorithm that converges to the entropy [19], [23], [24], and shows a robust performance when applied to correlated sequences [25] (see Materials and Methods).