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Titlebook: Universal Compression and Retrieval; Rafail Krichevsky Book 1994 Springer Science+Business Media B.V. 1994 Boolean function.Moore.Shannon.

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发表于 2025-3-21 17:22:57 | 显示全部楼层 |阅读模式
书目名称Universal Compression and Retrieval
编辑Rafail Krichevsky
视频video
丛书名称Mathematics and Its Applications
图书封面Titlebook: Universal Compression and Retrieval;  Rafail Krichevsky Book 1994 Springer Science+Business Media B.V. 1994 Boolean function.Moore.Shannon.
描述Objectives Computer and communication practice relies on data compression and dictionary search methods. They lean on a rapidly developing theory. Its exposition from a new viewpoint is the purpose of the book. We start from the very beginning and finish with the latest achievements of the theory, some of them in print for the first time. The book is intended for serving as both a monograph and a self-contained textbook. Information retrieval is the subject of the treatises by D. Knuth (1973) and K. Mehlhorn (1987). Data compression is the subject of source coding. It is a chapter of information theory. Its up-to-date state is presented in the books of Storer (1988), Lynch (1985), T. Bell et al. (1990). The difference between them and the present book is as follows. First. We include information retrieval into source coding instead of discussing it separately. Information-theoretic methods proved to be very effective in information search. Second. For many years the target of the source coding theory was the estimation of the maximal degree of the data compression. This target is practically bit today. The sought degree is now known for most of the sources. We believe that the next
出版日期Book 1994
关键词Boolean function; Moore; Shannon; algorithms; communication; complexity; computer; computer science; data co
版次1
doihttps://doi.org/10.1007/978-94-017-3628-2
isbn_softcover978-90-481-4357-3
isbn_ebook978-94-017-3628-2
copyrightSpringer Science+Business Media B.V. 1994
The information of publication is updating

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发表于 2025-3-21 21:03:24 | 显示全部楼层
Universal Codes,are ordered). There are both blockto-variable-length and variable-length-to-block universal codes. There is a sequence of codes, which is weakly universal on the set of all stationary sources (the redundancy goes to zero).
发表于 2025-3-22 01:58:18 | 显示全部楼层
Source Coding,s per an input letter is the encoding cost. The difference between the encoding cost and the source entropy is the redundancy, which is nonnegative for decipherable codes. So, the entropy is the cost of an ideal encoding. There are different methods to bring the cost closer to the entropy. For none
发表于 2025-3-22 05:34:36 | 显示全部楼层
Universal Codes,versal codes are constructed explicitly for some interesting sets of sources. Those are Bernoulli, Markov, monotone sources (probabilities of letters are ordered). There are both blockto-variable-length and variable-length-to-block universal codes. There is a sequence of codes, which is weakly unive
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发表于 2025-3-22 14:20:08 | 显示全部楼层
Optimal Numerator,d, their sizes are not optimal. In this chapter we will combine elementary numerators with numerators produced by exhaustive search over small-sized dictionaries. We will aim at three targets. First, the size of the numerator obtained should be small. Second, the numerator should be simple enough to
发表于 2025-3-22 18:24:30 | 显示全部楼层
Book 1994 exposition from a new viewpoint is the purpose of the book. We start from the very beginning and finish with the latest achievements of the theory, some of them in print for the first time. The book is intended for serving as both a monograph and a self-contained textbook. Information retrieval is
发表于 2025-3-22 23:01:52 | 显示全部楼层
heory. Its exposition from a new viewpoint is the purpose of the book. We start from the very beginning and finish with the latest achievements of the theory, some of them in print for the first time. The book is intended for serving as both a monograph and a self-contained textbook. Information ret
发表于 2025-3-23 05:21:18 | 显示全部楼层
Introduction,There are two types of information sources. A combinatorial source produces a subset of words. A stochastic source can produce each word with a probability. We distinguish finite memory (Markov), zero memory (Bernoulli), stationary sources.
发表于 2025-3-23 09:31:25 | 显示全部楼层
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