Download Compression-Based Methods of Statistical Analysis and by Boris Ryabko, Jaakko Astola, Mikhail Malyutov PDF

By Boris Ryabko, Jaakko Astola, Mikhail Malyutov

Universal codes successfully compress sequences generated by way of desk bound and ergodic resources with unknown facts, they usually have been initially designed for lossless information compression. meanwhile, it was once discovered that they are often used for fixing vital difficulties of prediction and statistical research of time sequence, and this e-book describes fresh ends up in this area.

The first bankruptcy introduces and describes the applying of common codes to prediction and the statistical research of time sequence; the second one bankruptcy describes purposes of chosen statistical the right way to cryptography, together with assaults on block ciphers; and the 3rd bankruptcy describes a homogeneity attempt used to figure out authorship of literary texts.

The e-book can be helpful for researchers and complicated scholars in info thought, mathematical information, time-series research, and cryptography. it really is assumed that the reader has a few grounding in statistics and in details theory.

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Extra info for Compression-Based Methods of Statistical Analysis and Prediction of Time Series

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Denote the partitioning of the interval ŒA; B into n equal subintervals as ˘n . 19). t ntC1 /, t ! 1, where n is the number of subintervals in the partition, and t is the length of the row x1 : : : xt . t3 ntC2 /, t ! 1. So, we can see that the number of the subintervals of the partition (n) determines the complexity of the algorithm. It turns out that the complexity can be reduced if n is large. 19)) coincide allows us to use the method of grouping of alphabet letters from [38]. In this case, the reduction of complexity cannot be described analytically since this value, generally speaking, depends on the considered time series.

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