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Entropy and complexity of finite sequences as fluctuating quantities

机译:波动序列的有限序列的熵和复杂性

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The paper is devoted to the analysis of digitized sequences of real numbers and discrete strings, by means of the concepts of entropy and complexity. Special attention is paid to the random character of these quantities and their fluctuation spectrum. As applications, we discuss neural spike-trains and DNA sequences. We consider a given sequence as one realization of finite length of certain random process. The other members of the ensemble are defined by appropriate surrogate sequences and surrogate processes. We show that n-gram entropies and the context-free grammatical complexity have to be considered as fluctuating quantities and study the corresponding distributions. Different complexity measures reveal different aspects of a sequence. Finally, we show that the diversity of the entropy (that takes small values for pseudorandom strings) and the context-free grammatical complexity (which takes large values for pseudorandom strings) give, nonetheless, consistent results by comparison of the ranking of sample sequences taken from molecular biology, neuroscience, and artificial control sequences. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved. [References: 41]
机译:本文通过熵和复杂度的概念致力于实数和离散字符串的数字化序列的分析。要特别注意这些量的随机性及其波动范围。作为应用,我们讨论了神经刺突和DNA序列。我们将给定序列视为某种随机过程有限长度的一种实现。合奏的其他成员由适当的代理序列和代理过程定义。我们表明,n元语法熵和上下文无关的语法复杂性必须被视为波动量,并研究相应的分布。不同的复杂性度量揭示了序列的不同方面。最后,我们证明了熵的多样性(对于伪随机字符串取较小的值)和上下文无关的语法复杂度(对于伪随机字符串取较大的值),通过比较采样序列的等级得出了一致的结果来自分子生物学,神经科学和人工控制序列。 (C)2002 Elsevier Science Ireland Ltd.保留所有权利。 [参考:41]

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