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Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024

Maximum Entropy, Information without Probability and Complex Fractals
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Jumarie, Guy 作者
譯者
2000-5 出版日期
289 頁數
$ 202.27 價格
叢書系列
9780792363309 圖書編碼

Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 圖書標籤: stochastic   

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發表於2024-10-03

Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 用戶評價

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Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 著者簡介

Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 著者簡介

Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Maximum Entropy, Information without Probability and Complex Fractals 在線電子書 圖書描述

This book presents material on three topics, namely the amount of information involved in non-random functions, the amount of information involved in non-probabilistic square matrices (i.e. which are not quantum density matrices), and a new model of complex-valued fractional Brownian motion of order n defined via random walks in the complex plane. These three subjects, which on the surface have no common features, are, in fact, direct consequences of the maximum entropy principle. Moreover, information on non-random functions and complex fractional Brownian motion are directly related to fractals. Thus, a unified framework is constructed which encompasses information with and without probability, quantum information of square matrices with and without probabilistic meaning, and fractals in the complex plane. This volume also features many applications. Audience: This work is intended for theoretical and mathematical physicists, but also for applied mathematicians, experimental physicists, communication engineers, electrical engineers, practitioners in pattern recognition and computer vision, control systems engineers, and theoretical biologists.

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