Varotsos P A, Sarlis N V, Skordas E S
Solid State Section, Physics Department, University of Athens, Panepistimiopolis, Zografos, Athens 157 84, Greece.
Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Sep;68(3 Pt 1):031106. doi: 10.1103/PhysRevE.68.031106. Epub 2003 Sep 23.
Three types of electric signals were analyzed: Ion current fluctuations in membrane channels (ICFMC), Seismic electric signals activities (SES), and "artificial" noises (AN). The wavelet transform, when applied to the conventional time domain, does not allow a classification of these signals, but does so in the "natural" time domain. A classification also becomes possible, if we study <chi(q)>-
膜通道中的离子电流波动(ICFMC)、地震电信号活动(SES)和“人工”噪声(AN)。当将小波变换应用于传统时域时,无法对这些信号进行分类,但在“自然”时域中却可以。如果我们研究<χ(q)>-<χ>(q)与q的关系(其中χ代表“自然”时间),也能够实现分类。对于大约在1到2之间的q值,信号可以被分类,且ICFMC介于其他两种类型之间。对于q = 1,ICFMC的“熵”S等同于<χlnχ>-<χ>ln<χ>,几乎等于“均匀”分布的熵,而AN和SES的S值分别更大和更小。重新审视了最近[P. 瓦罗托斯、N. 萨利斯和E. 斯科尔达斯,《物理评论E》67, 021109 (2003)]的发现,即在短时间尺度上,SES和AN(已证明是非马尔可夫的)在去趋势波动分析中产生的指数α在(1.0, 1.5)范围内。即使是一个马尔可夫二分时间序列,在短时间尺度上也会导致类似的α指数。