Wallace Rodrick, Leonova Irina, Gochhait Saikat
The New York State Psychiatric Institute, 1051 Riverside Dr, New York, NY 10032, USA.
Faculty of Social Sciences, Lobachevsky University, 603950 Nizhny Novgorod, Russia.
Entropy (Basel). 2022 Aug 3;24(8):1070. doi: 10.3390/e24081070.
A central conundrum enshrouds biocognition: almost all such phenomena are inherently unstable and must be constantly controlled by external regulatory machinery to ensure proper function, in much the same sense that blood pressure and the 'stream of consciousness' require persistent delicate regulation for the survival of higher organisms. Here, we derive the Data Rate Theorem of control theory that characterizes such instability via the Rate Distortion Theorem of information theory for adiabatically stationary nonergodic systems. We then outline a novel approach to building new statistical tools for data analysis based on those theorems, focusing on groupoid symmetry-breaking phase transitions characterized by Fisher Zero analogs.
几乎所有此类现象本质上都是不稳定的，必须由外部调节机制不断控制以确保正常功能，这与血压和“意识流”需要持续精细调节以维持高等生物生存的道理大致相同。在此，我们通过信息论的率失真定理推导出控制理论的数据率定理，该定理用于描述绝热静止非遍历系统中的此类不稳定性。然后，我们概述了一种基于这些定理构建新的数据分析统计工具的新颖方法，重点关注以费舍尔零点类似物为特征的广群对称破缺相变。
