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Record Nr. |
UNINA9910254990103321 |
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Autore |
Ryabko Boris |
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Titolo |
Compression-based methods of statistical analysis and prediction of time series / / by Boris Ryabko, Jaakko Astola, Mikhail Malyutov |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (153 p.) |
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Disciplina |
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Soggetti |
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Data structures (Computer science) |
Computer science—Mathematics |
Natural language processing (Computer science) |
Statistics |
Computational linguistics |
Data Structures and Information Theory |
Mathematics of Computing |
Natural Language Processing (NLP) |
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
Computational Linguistics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Statistical Methods Based on Universal Codes -- Applications to Cryptography -- SCOT-Modeling and Nonparametric Testing of Stationary Strings. |
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Sommario/riassunto |
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Universal codes efficiently compress sequences generated by stationary and ergodic sources with unknown statistics, and they were originally designed for lossless data compression. In the meantime, it was realized that they can be used for solving important problems of prediction and statistical analysis of time series, and this book describes recent results in this area. The first chapter introduces and describes the application of universal codes to prediction and the statistical analysis of time series; the second chapter describes applications of selected statistical methods to cryptography, including |
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attacks on block ciphers; and the third chapter describes a homogeneity test used to determine authorship of literary texts. The book will be useful for researchers and advanced students in information theory, mathematical statistics, time-series analysis, and cryptography. It is assumed that the reader has some grounding in statistics and in information theory. |
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