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图论

Graph Theory
课程网址: http://videolectures.net/netadis2013_monasson_graph_theory/  
主讲教师: Rémi Monasson
开课单位: 国家科学研究中心
开课时间: 2013-11-21
课程语种: 英语
中文简介:
随机图在概率论、组合学和统计物理学中具有中心重要性。这些讲座的目的是以一种非严格的方式复习随机图的典型性质,重点是Erdos-Renyi(鄂尔多斯-雷尼)集合。我们将在布尔方程随机系统的特殊情况下说明这些性质,特别是渗透跃迁。统计力学技术将被引入研究稀有性质,即与典型情况的大偏差。在第二讲中,我们将聚焦于动态过程对随机图结构的修改,并分析它们的演化。此外,还将介绍“稀释”系统的复制方法。最后,在第三讲中,随机空间地图将被考虑,与神经生物学中最近的实验建模的关系。 第1讲:随机图的典型和稀有性质 第2讲:随机图的动态过程 讲座3:Hopfield-like模型中空间地图的存储。模型相图的统计力学推导详见本文。 进一步阅读建议: B. Bollobas,随机图,剑桥大学出版社(2001) N.C. Wormald,随机图过程和贪心算法的微分方程方法,《近似和随机算法讲座》(M. Karonski和H.J. Proemel主编),第73-155页。PWN,华沙(1999年) D.J. Amit,大脑功能建模:吸引子神经网络的世界,剑桥大学出版社(1992) 有关统计力学和随机布尔系统的更多信息,请参阅R. Monasson,《随机优化问题中的相变导论》,Les Houches暑期学校讲义,Elsevier(2006)和其中的参考文献。
课程简介: Random graphs are of central importance in probability theory, combinatorics, and statistical physics. The purpose of these lectures is to review, in a non-rigorous manner, the typical properties of random graphs, with a strong emphasis on the Erdos-Renyi ensemble. We will illustrate those properties, and in particular the percolation transition, on the special case of random systems of Boolean equations. Statistical mechanics techniques will be introduced to study rare properties, that is, large deviations from the typical case. In the second lecture we will focus on dynamical processes modifying random graph structures, and analyze their evolution. Furthermore the replica method for 'dilute' systems will be presented. Finally, in the third lecture, random spatial maps will be considered, in relationship with the modeling of recent experiments in neurobiology. Lecture 1: Typical and Rare Properties of Random Graphs Lecture 2: Dynamical Processes on Random Graphs Lecture 3: Storage of spatial maps in Hopfield-like models. For details about the statistical mechanics derivation of the phase diagram of the model, see this paper. Suggestions for further readings: B. Bollobas, Random Graphs, Cambridge University Press (2001) N.C. Wormald, The differential equation method for random graph processes and greedy algorithms, in Lectures on Approximation and Randomized Algorithms (M. Karonski and H.J. Proemel, eds), pp. 73-155. PWN, Warsaw (1999) D.J. Amit, Modeling Brain Function: The World of Attractor Neural Networks, Cambridge University Press (1992) for more on statistical mechanics and random Boolean systems, see R. Monasson, Introduction to Phase Transitions in Random Optimization Problems, Lecture Notes of Les Houches Summer School, Elsevier (2006) and references therein.
关 键 词: 随机图论; 布尔方程; 随机系统; 渗透迁跃
课程来源: 视频讲座网
数据采集: 2023-04-22:chenxin01
最后编审: 2023-05-18:chenxin01
阅读次数: 43