Compression-Based Methods of Statistical Analysis and Prediction of Time Series
暫譯: 基於壓縮的時間序列統計分析與預測方法

Boris Ryabko, Jaakko Astola, Mikhail Malyutov

  • 出版商: Springer
  • 出版日期: 2016-05-27
  • 售價: $3,970
  • 貴賓價: 9.5$3,772
  • 語言: 英文
  • 頁數: 144
  • 裝訂: Hardcover
  • ISBN: 3319322516
  • ISBN-13: 9783319322513
  • 海外代購書籍(需單獨結帳)

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商品描述

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 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.

商品描述(中文翻譯)

通用編碼有效地壓縮由具有未知統計特性的平穩和遍歷來源生成的序列,最初是為了無損數據壓縮而設計的。與此同時,人們意識到它們可以用於解決預測和時間序列統計分析的重要問題,本書描述了該領域的最新成果。

第一章介紹並描述了通用編碼在預測和時間序列統計分析中的應用;第二章描述了選定統計方法在密碼學中的應用,包括對區塊加密的攻擊;第三章描述了一種用於確定文學文本作者的同質性測試。

本書將對信息理論、數學統計、時間序列分析和密碼學的研究人員和高級學生有所幫助。假設讀者對統計學和信息理論有一定的基礎。