The more microstates, or ways of ordering a system, the more entropy the system has.This article is of interest to the following WikiProjects:This page contains Frontiers open-access articles about New synonym. Verb, non-3rd person singular present. If the change in entropy is negative, energy has been given off. A chunk of ice has low entropy because its molecules are frozen in place.
1 noun entropy physics: measure of disorder 1 noun entropy chaos, disorder 1 noun Definition of entropy in Technology (theory) A measure of the disorder of a system.This article has been rated as Start-Class on the project's quality scale.Synonyms for entropy at english dictionary. Computing Wikipedia:WikiProject Computing Template:WikiProject Computing Computing articlesare the shannon entropy and residual entropy synonyms h r 0 marko popovic department of chemistry and biochemistry, byu, provo, ut 84602, popovic.pasagmail.comnoun entropy A thermodynamic quantity representing the unavailability of a systems thermal energy for conversion into mechanical work, often interpreted as the degree of disorder or randomness in the system. If you would like to participate, please visit the project page, where you can join the discussion and see a list of open tasks. Another Words of Shannon entropyGenerally speaking, this idiom 'Shannon entropy' can be This article is within the scope of WikiProject Computing, a collaborative effort to improve the coverage of computers, computing, and information technology on Wikipedia. As you can see, not only synonyms and antonyms, but also hypernyms, hyponyms, meronyms, anagrams, holonyms, idioms phrases, homorhymes, homophones, prefixes and suffixes.
4 Entropy can not be a measure of similarity 1 Isn't "entropy coding" the same thing as "lossless compression"? Computer science Wikipedia:WikiProject Computer science Template:WikiProject Computer science Computer science articlesThis article has been rated as Mid-importance on the project's importance scale.Things you can help WikiProject Computer science with: If you would like to participate, please visit the project page, where you can join the discussion and see a list of open tasks. Thermodynamics strictly thermodynamic entropy.This article has been rated as Low-importance on the project's importance scale.This article is within the scope of WikiProject Computer science, a collaborative effort to improve the coverage of Computer science related articles on Wikipedia.
I have never previously heard anyone assert that LZ coding or other such things are not entropy coding. In the usage I have experienced, the terms "entropy coding" and "lossless compression" are synonymous, and both terms apply to such things as Lempel-Ziv coding. - Antaeus Feldspar 20:43, (UTC) Actually, I don't know where Feldspar gets his definitions, but I mostly agree with the prior comment by 4.65.146.242. LZ77 compression, for instance, is an important compression technique that isn't any form of entropy encoding. - comments by 4.65.146.242 moved from article Entropy encoding is only a subset of lossless compression. Also "entropy coding" would be better a better subject title than "entropy encoding".
People might use "entropy coding" as if it was a synonym of "lossless compression" (just as there are some major RFCs that incorrectly use "Huffman code" as if it was a synonym of "prefix code", instead of denoting only to those prefix codes created by a Huffman algorithm) but that's definitely not correct usage. Pawnbroker 05:28, (UTC) Then I don't know where you get your definitions, Pawn. I also agree that "entropy coding" is better than "entropy encoding". For example, I don't think what it describes is a very accurate description of what happens in arithmetic coding.
In fact, when the input symbols are not probabilistically independent of each other (e.g., when there is some statistical dependency between input symbol values, as there is with text, for example) any simple one-to-one mapping like a Huffman code will be inferior to methods that take into account the inter-symbol dependencies. Many of those ways do not involve a mapping of individual input symbols to specific coded lengths. Those ways include techniques like LZW coding and other dictionary-based methods. There are many ways to make the average approach the entropy (or at least be substantially less than the average number of bits used to represent the input to the entropy encoding process).
Thus the above Feldspar quote that "each symbol is assigned a pattern whose length/cost corresponds to its entropy" is not correct in that sense. The average amount of information per symbol is the entropy. The negative log of the probability of the sample value (assuming independent source symbol statistics) is the "information" conveyed by that sample value. Entropy is the expected value of the negative log of the probability, not the actual value of the negative log of the probability associated with a particular symbol's value. Entropy includes the concept of averaging over all possible values of the input symbol. Pawnbroker 23:29, (UTC) Note also that entropy of a symbol is not the same thing as the negative log of the probability of the symbol value.
The second text is the sequence A-Z followed by the reverse of that sequence, Z-A. The first text is the sequence A-Z, followed by A-Z again. A simple example: Create two texts, each of which uses the characters A-Z twice. Pawnbroker 23:52, (UTC) A little clear thinking will make it clear that Lempel-Ziv does not fit into the quoted definition, since it is entirely the existence of repeated multi-symbol patterns that enables compression under this technique, which has absolutely no connection with the entropy of the input symbols save as the existence of repeated multi-symbol patterns requires the repetition of the component symbols. Entropy coding therefore is conceptually focused on good average behavior on typical data, not at what happens from the micro perspective of individual symbols and individual short message lengths.
Actually, the existence of repeated patterns is very much coupled with the concept of entropy. If you assume a probabilistic source model that, with equal probability, generates either the sequence A to Z or the sequence Z to A in each stage of its operation, then it can easily be shown that either LZ coding or any other good entropy coder will approach the underlying entropy after a long run of input data (much more than two 26-letter sequences), which is a rate of one bit per 26 letters. 52 letters is also way too short a message to try to invoke probabilistic behaviour arguments. - Antaeus Feldspar 00:22, (UTC) Those are artifically-constructed example sequences - they are not generated by a probabilistic source model, so it is impossible to talk about their entropy. Right now the assertion that there's no difference between the two terms is completely unsupported by published sources.
Some proofs of Shannon's lossless coding theorem involve segmenting the source in this fashion (something known as the "asymptotic equi-partition property"). Certain patterns will be "typical" and others will be highly atypical.
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