论文标题
基于关节置换的时间不可逆性和振幅不可逆性的比较分析
Comparative analysis of time irreversibility and amplitude irreversibility based on joint permutation
论文作者
论文摘要
尽管时间不可逆性（TIR）和振幅不可逆性（空气）是非平衡分析的相关概念，但他们的关联很少受到关注。本文根据统计描述和数值模拟对TIR和空气之间的关系进行系统的比较分析。为了简化TIR和空气的量化，将相关向量的幅度排列和全局信息组合在一起，以产生联合概率估计。 Chaotic Logistic，Henon和Lorenz系列是根据替代理论评估TIR和空气的，并且测量了这些模型系列的关节排列的分布，以比较TIR和空气的程度。然后，将关节置换TIR和空气用于研究癫痫脑电图数据中的非平衡病理特征。测试结果表明，癫痫发作的脑电活动，尤其是在癫痫发作时表现出较高的非平衡特征。根据混沌模型数据中的统计定义和靶向关节排列对，TIR和空气分别与时间和振幅可逆性分别不同的非平衡描述符，因此需要不同形式的数值分析。同时，TIR和空气都提供了与非平衡过程相关的波动定理的措施，并且在用于分析模型系列和现实世界信号时，关节置换对和一致的结果都具有相似的概率差异。总体而言，对TIR和空气的比较分析有助于我们对非平衡特征的理解，并扩大了定量非平衡度量的范围。此外，关节排列的构建有助于符号时间序列分析的发展。
Although time irreversibility (TIR) and amplitude irreversibility (AIR) are relevant concepts for nonequilibrium analysis, their association has received little attention. This paper conducts a systematic comparative analysis of the relationship between TIR and AIR based on statistical descriptions and numerical simulations. To simplify the quantification of TIR and AIR, the amplitude permutation and global information of the associated vector are combined to produce a joint probability estimation. Chaotic logistic, Henon, and Lorenz series are generated to evaluate TIR and AIR according to surrogate theory, and the distributions of joint permutations for these model series are measured to compare the degree of TIR and AIR. The joint permutation TIR and AIR are then used to investigate nonequilibrium pathological features in epileptic electroencephalography data. Test results suggest that epileptic brain electrical activities, particular those during the onset of seizure, manifest higher nonequilibrium characteristics. According to the statistical definitions and targeted pairs of joint permutations in the chaotic model data, TIR and AIR are fundamentally different nonequilibrium descriptors from time- and amplitude-reversibility, respectively, and thus require different forms of numerical analysis. At the same time, TIR and AIR both provide measures for fluctuation theorems associated with nonequilibrium processes, and have similar probabilistic differences in the pairs of joint permutations and consistent outcomes when used to analyze both the model series and real-world signals. Overall, comparative analysis of TIR and AIR contributes to our understanding of nonequilibrium features and broadens the scope of quantitative nonequilibrium measures. Additionally, the construction of joint permutations contributes to the development of symbolic time series analysis.
