Percolation Model of Phase Transitions in the Central Nervous Systems during Perceptual Information Processing

感知信息处理过程中中枢神经系统相变的渗透模型

• 批准号: 0130352
• 负责人: Robert Kozma
• 金额: $ 65.22万
• 依托单位: University of Memphis
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-02-01 至 2006-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0130352&HistoricalAwards=false
• 关键词: Percolation; Model; Phase; Transitions; Central

EIA-0130352-Robert Kozma-University of Memphis-Percolation Model of Phase Transitions in the Central Nervous Systems during Perceptual Information Processing The proposed research will explore the close link between pattern-based information processing using dynamical memories and percolation phenomena. Percolation models have been used to analyze a wide range of processes in physics and electronics, and in biological and ecological systems. In the last decade and a half, many variants of the standard percolation models have been studied. In particular, there has been much work on the family or processes known as bootstrap percolation. Computer experiments performed by physicists have suggested interesting non-trivial models. The solid mathematical theory of percolation in lattices to lay down the foundations of dynamical memories and the related phase transitions will be applied.

EIA-0130352-Robert Kozma-University of Memphis-Percolation Model of Phase Transitions in the Central Nervous Systems during the Perceptual Information Processing拟议的研究将探索使用动态记忆和渗透现象的基于模式的信息处理之间的密切联系。 渗滤模型已被用于分析物理学和电子学以及生物和生态系统中的广泛过程。 在过去的十五年中，人们研究了标准渗流模型的许多变体。 特别是，已经有很多工作的家庭或过程称为自举渗滤。 物理学家进行的计算机实验提出了有趣的非平凡模型。 坚实的数学理论的渗透晶格奠定了基础的动态记忆和相关的相变将被应用。