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The information bottleneck method is a technique in information theory introduced by Naftali Tishby, Fernando C. Pereira, and William Bialek. [1] It is designed for finding the best tradeoff between accuracy and complexity (compression) when summarizing (e.g. clustering) a random variable X, given a joint probability distribution p(X,Y) between X and an observed relevant variable Y - and self ...
The Burroughs Large Systems Group produced a family of large 48-bit mainframes using stack machine instruction sets with dense syllables. [NB 1] The first machine in the family was the B5000 in 1961, which was optimized for compiling ALGOL 60 programs extremely well, using single-pass compilers. The B5000 evolved into the B5500 (disk rather ...
In information theory, data compression, source coding, [1] or bit-rate reduction is the process of encoding information using fewer bits than the original representation. [2] Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in ...
Despite the copyrighted nature of the CPT code sets, the use of the code is mandated by almost all health insurance payment and information systems, including the Centers for Medicare and Medicaid Services (CMS), and the data for the code sets appears in the Federal Register. It is necessary for most users of the CPT code (principally providers ...
Shannon developed information entropy as a measure for the uncertainty in a message while essentially inventing the field of information theory. The binary Golay code was developed in 1949. It is an error-correcting code capable of correcting up to three errors in each 24-bit word, and detecting a fourth.
It is common in information theory to speak of the "rate" or "entropy" of a language. This is appropriate, for example, when the source of information is English prose. The rate of a memoryless source is simply (), since by definition there is no interdependence of the successive messages of a memoryless source. [citation needed]
The input–process–output model. The input–process–output (IPO) model, or input-process-output pattern, is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or other process.
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 ...