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Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data ...
In information theory, the source coding theorem (Shannon 1948) [2] informally states that (MacKay 2003, pg. 81, [3] Cover 2006, Chapter 5 [4]): N i.i.d. random variables each with entropy H(X) can be compressed into more than N H(X) bits with negligible risk of information loss, as N → ∞; but conversely, if they are compressed into fewer than N H(X) bits it is virtually certain that ...
The Weissman score is a performance metric for lossless compression applications. It was developed by Tsachy Weissman, a professor at Stanford University, and Vinith Misra, a graduate student, at the request of producers for HBO's television series Silicon Valley, a television show about a fictional tech start-up working on a data compression algorithm.
In the field of data compression, Shannon coding, named after its creator, Claude Shannon, is a lossless data compression technique for constructing a prefix code based on a set of symbols and their probabilities (estimated or measured).
Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.
Van Jacobson Header Compression (also VJ compression, or just Header Compression) is an option in most versions of PPP. Versions of Serial Line Internet Protocol (SLIP) with VJ compression are often called CSLIP (Compressed SLIP).
The reduction of the time needed to transmit a given amount of data in a given bandwidth. Bandwidth compression implies a reduction in normal bandwidth of an information-carrying signal without reducing the information content of the signal. This can be accomplished with lossless data compression techniques.
Downloading large amounts of data over the Internet for software updates can induce high network traffic problems, especially when a network of computers is involved. Binary Delta Compression technology allows a major reduction of download size by only transferring the difference between the old and the new files during the update process.