bat365在线平台网站

R. Nigmatullin教授:Detection of self-similar and quasi-periodic processes in complex systems: How quantitatively to describe their behavior?

发布日期:2016-04-25

报告题目:

Detection of self-similar and quasi-periodic processes in complex systems: How quantitatively to describe their behavior?

报告人:

R. Nigmatullin教授

俄罗斯喀山联邦大学 Kazan (Volga region) Federal University

邀请人:

王春雷 教授

报告时间:

2014-04-18 13:30

报告地点:

知新楼 B座1248

报告内容提示:

Part 1. A new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth's mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. The general conditions of application of this fitting method describing the response of many complex systems and the forecast possibilities are discussed.

Part 2. It has been shown that in nature at least two general scenarios of data structuring are possible: (a) self-similar scenario when the measured data form a self-similar (SS) structure; (b) quasi-periodic scenario when the repeated (strongly-correlated) data form random sequences that are almost periodic with respect to each other. In the second case it becomes possible to describe their behavior and express a part of their randomness quantitatively in terms of the deterministic amplitude-frequency response (AFR) belonging to the generalized Prony's spectrum (GPS). This possibility allows to reexamine the conventional concept of measurements and opens a new way for description of a wide set of different data. In particular, it concerns different complex systems when the “best fit” model pretending to description of the data measured is absent but the barest necessity of description of these data in terms of the reduced number of quantitative parameters exists. The possibilities of the proposed approach and detection algorithm of the quasi-periodic (QP) processes were demonstrated on actual data: spectroscopic data recorded for pure water and acoustic data for a test hole. The suggested methodology allows revising the accepted classification of different incommensurable and self-affine spatial structures and finding accurate interpretation of the generalized Prony’s spectroscopy that includes the Fourier spectroscopy as a partial case.

报告人简介:

尼格马图林教授,科学博士, 俄罗斯喀山联邦大学物理研究所 理论物理系。尼格马图林教授出生于1947年俄罗斯联邦鞑靼斯坦共和国的首府喀山。于1973年在喀山州立大学获得博士学位,然后于1993年在同一所大学获得物理和数学博士学位。 现在是喀山联邦大学(伏尔加区)的物理数学全职教授。1982-1983年期间,在英国Jonscher教授的实验室从事电介质物理研究。从1990年起,成为国际电介质协会的成员。1998年他和法国同事A. Le Mehaute 博士和L. Nivanen博士一起出版了关于分形几何和分数阶微积分的专著。目前的研究兴趣是电介质物理,发展S/N处理分析的新方法以及分数阶微积分和分形几何在不同物理领域的应用。他已经发表了220余篇论文,SCI引用超过1800次,H-因子17。是2012年南京召开第五届分数阶微积分及其应用国际会议的plenary speaker之一,http://em.hhu.edu.cn/fda12/Committees.html

欢迎感兴趣的师生参加!